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H: Where and how to do large scale supervised machine learning?
I'm beginner in ML and I have a large dataset that has 15 features with 6M rows, so it becomes challenging to work on it locally. I can train one model locally but to perform hyper parameter tuning and cross validations with my macbook pro, it runs out of... |
H: Using batchnorm and dropout simultaneously?
I am a bit confused about the relation between terms "Dropout" and "BatchNorm". As I understand,
Dropout is regularization technique, which is using only during training.
BatchNorm is technique, which is using for accelerating training speed, improving accuracy and e.t.... |
H: LSTM for regression in time and space
I am trying to implement my first LSTM for a supervised regression problem.
The data is in the following format: every row has month, day and hour in three separate columns, other 10 predictive features and one output.
Of those 10 predictive features, two are the coordinates in... |
H: Does it make sense to use UMAP for dimensionality reduction for modeling (rather then presentation/exploration)?
Reducing dimensionality via PCA before training is a common practice, but PCA cannot makes use of nonlinear relations between features.
I read about UMAP (e.g. https://adanayak.medium.com/dimensionality-... |
H: How to know if a time series sequence is predictibale or just random (Univariate time series prediction)?
I'm trying to predict a current value of a variable based on the its previous 10 values. I tried multiple time series approaches including ARIMA, LSTM and linear regression... None of them really performed well... |
H: How to use efficient net as feature extractor for meta/Few shot learning in PyTorch
I am working on few shot learning and I wanted to use efficient-net as backbone feature extractor. Most of the model use Resnet as feature extractor. For example I can use below line of code and it extract features for me -
from mod... |
H: How can compare suggestion models with different performances?
I have 4 class binary classification models. That models identify which class a particular students is suitable for.
For example, we have user 1 and 4 classes recommendation model.
Models were identify how this user would like to take its class.
By rea... |
H: Calculating confidence interval for model accuracy in a multi-class classification problem
In the book Applied Predictive Modeling by Max Kuhn and Kjell Johnson, there is an exercise concerning the calculation of a confidence interval for model accuracy. It reads as follows.
One method for understanding the uncerta... |
H: LogCoshLoss on pytorch
Hi I am currently testing multiple loss on my code using PyTorch, but when I stumbled on log cosh loss function I did not find any resources on the PyTorch documentation unlike Tensor flow which have as build-in function
is it excite in Pytorch with different name ?
AI: Yes the pytroch is not... |
H: How to compare models and which settings to keep constant?
I already posted this in another forum but no response. So, posting it here.
Currently, in clinical practice, clinicians use a score (as a single feature) to predict the mortality of a patient. Now in my project based on clinician inputs, we have created tw... |
H: How can I aggregate/combine 3 columns of a data frame into one column with the sum of the values of the other three in R?
Part of my dataset is shown in this image, I want to combine the columns GR_S01_w1_a, GR_S01_w1_b and GR_S01_w1_c into a single column - GR_S01_w1 - whose values are the sum of the three.
I kno... |
H: TypeError: __init__() missing 1 required positional argument: 'num_features'
I was trying to denoise image using Deep Image prior. when I use ResNet as an architecture i am getting error.
INPUT = 'noise' # 'meshgrid' get_noise function
pad = 'reflection'
OPT_OVER = 'net' # 'net,input'
reg_noise_std = 1./... |
H: Shapley value, conditional expectation vs reference point
In Shapley, the marginal contribution of a feature is computed by comparing the performance of a model with and without a feature over all possible subsets of features.
A common choice is using the average value of a feature, when such feature is not present... |
H: Meaning of the covariance matrix?
I wonder about the excessive usage of the covariance matrix across all kinds of machine learning tools. So far, for me, the covariance is just a pre-step to get to the correlation. And as there is an obvious reason for the correlation itself, I wonder why I encounter the covariance... |
H: How to design a model for contour recognition? In particular, how to shape the output layer?
I want to design and train a neural network for the automatic recognition of the edges, in some microscopic images.
I am using Keras for a start, I may consider PyTorch later.
The structure of the images is rather simple, w... |
H: CNN: training accuracy vs. validation accuracy
I just finished training two models, while the one is pretrained and the other trained from scratch and created two diagrams afterward with their data, but as I am very new to machine learning, I don't get what they state.
Why is the training accuracy so low? Did I use... |
H: How do I find pairwise maximum of multiple rows in a column using python?
I have a column with float values. The column has 300 rows. I want to get the pairwise max of each row with the row below it. For example: if my column has 2, 25, 1, 24 as row values, I want to find max of 2 and 25, then max of 25 and 1 and s... |
H: How to train 3 models with single loss function in pytorch
optimizer=torch.optim.AdamW(list(model3.parameters())+list(model1.parameters())+list(model2.parameters()))
optimizer.zero_grad()
prediction=model3(model1(x)+model2(x))
loss=nn.BCELoss(prediction,labels)
loss.backward()
optimizer.step()
How can I upd... |
H: How can i extract words from a single concatenated word?
I'm stuck on this problem and would love some input.
I have mulitple words such as getExtention, getPath, someWord or someword and i want to separate each concatinated words into its own words such as:
getExtention ---> [get][Extention].
someword --> [some][w... |
H: Gradient descent method
If we suppose that this is formula for gradient descent method:
$$x_{n+1}=x_n-\lambda\cdot{{df(x)}\over{dx}},\ n=0,1,2,3,...$$
Since there is no exact value that we subtract instead of derivative, does it mean that we subtract value of derivative and use it only for controlling direction of ... |
H: Classification report and confusion matrix problem
I am working on sign language recognition system using HOG and KNN. I have 26 classes of 180 images per class. The dataset was split into 1/3(67%) for tanning and 2/3(33%) testing after feature extraction with HOG. Model achieved recognition accuracy of 95% on test... |
H: Should I train from scratch or use pre-trained weights?
With yolov4, I am training an 80k images dataset that is used to classify different species of fish. Currently, I am using the following pre-trained weights: yolov4.conv.137 .
Now I was wondering if this is a backbone or weights trained with the COCO dataset?
... |
H: Can I set the rewards of a multi armed bandit problem with deterministic values?
I am new to reinforcement learning and I am tryng to understand the multi armed bandit problem.
I think I have understood that it consists in choosing the bandit that maximizes the future reward.
My doubt is in the implementation. In a... |
H: An universal sentence encoder for a specific language?
I am making a model that uses encoded articles (multiple sentences). I have found the Universal Sentence Encoder by Tensorflow, but it says it is only for English. Specifically, I am looking for an encoder for the Macedonian language. Can I use this encoder and... |
H: Can this dataset be separated linearly?
Is this dataset linearly separable? If not, can it be converted into one by applying some function as it seems to follow the same pattern?
Also, which classification algorithms could be used to fit this dataset?
AI: As Nikos said, the dataset is not linearly separable: one c... |
H: How to convert a dataframe into a single dictionary that is not nested?
I have a dataframe as below:
+----+----------------+-------------+----------------+-----------+
| | attribute_one| value_one | attribute_two | value_two |
|----+----------------+-------------+----------------+-----------|
| 0 | ma... |
H: What we can learn from the data if PCA scree plot bins are almost the same?
Suppose we have a data-set with 4 features.
Suppose we calculate the PCA for this dataset and we plot the scree-plot:
What we can learn from the features? Can we say that they are not linearly correlated? Can we say something else?
AI: In... |
H: Distance between any two points after DBSCAN
DBSCAN is a clustering model which is robust to detect the outliers also. A parameter $\epsilon$ i.e. radius is an input of the algorithm, a point is said to be outlier if it's circle with radius $\epsilon$ has no point except that point of center. I have detected the ou... |
H: Shared classifier for 3 neural networks (is this weights sharing?)
I would like to create 3 different VGGs with a shared classifier. Basically, each of these architectures has only the convolutions, and then I combine all the nets, with a classifier.
For a better explanation, let’s see this image:
I have no idea o... |
H: How should a stateless data transformation be applied in regard to train/test split?
I want to apply spatial sign transformation to my data, but unlike other transformations this one is stateless. I am using sklearn and normallly i would first use the .fit() function on training set and then .transfrom() on test se... |
H: What type of visualization is this and what are my options to produce something like it?
I am looking to reproduce the bottom part of the visualization below. What is this type of visualization called? What are my options to reproduce it? Preferably using Python or R, but I'm open to using other tools as well.
AI: ... |
H: Influence of label names on the classfierier perfromance
I am building a text classifier, the labels in my training data are not just short names like "Dog" or "Cat", they are more of lengthy sentences that range from 2 words to around 20 words.
Does the length of the label/class name affect the performance of the ... |
H: What are the advantages/disadvantages of using tfidf on n-grams generated through countvectorizer?
What are the advantages/disadvantages of using tfidf on n-grams generated through countvectorizer when your end goal is to see the frequent occurring terms in the corpus with the occurrence percentage?
AI: First, Coun... |
H: How to reshape or clean data to be able to visualize it with violin plots?
My end goal is to visualize some data using a violin plot or something similar using Python.
I have the following data in a file (test.csv). The first column is a list of species. The other columns determine abundance of the species at a cer... |
H: understanding pytorch pycoco tools object detection output
I am using pytorch vision library for object detection. I am using utilities provided for objection detection metrics. https://github.com/pytorch/vision. I am seeing following output
Epoch: [2] [0/10] eta: 0:00:50 lr: 0.000500 loss: 1.1589 (1.1589) los... |
H: How many training data should I use in multilabel classification?
Now I'm using Keras to implement a multi-label classification model. Specifically, I want to classify who present in an audio clip (maximal 8 people). The label of data has 8-bit, for example, [0,1,0,0,1,0,1,1]. It means totally the data should have ... |
H: Does Keras MultiHeadAttention with 1 head equals normal self attention?
Keras multihead attention if used as single head num_heads=1, then how is it different than Keras Attention ?
Also, Is multihead attention by default self-attention type?
AI: The Keras attention layer is a Luong attention block of type dot-p... |
H: How can the accuracy of the dictionary-based approach be measured and improved?
I recently used TextBlob and the NLTK library to do sentiment analysis. I used both dictionary-based and machine learning-based approaches. It is relatively easy to measure accuracy when we use machine learning approach, just define a t... |
H: Can landmark detection be only used for faces and human bodies?
I want to use landmark detection for finding specific points of interest in an indoor setting e.g. bedrooms, bathrooms etc. Is it possible to use it? So far I have only seen landmark detection being used for things like faces or human bodies. Any sugge... |
H: Does the abstraction of a class affects the performance of neural networks?
For example, if I have 3 audio classes including
Ambulance Siren
Police Car Siren
Firetruck Siren
assuming these 3 classes could be distinguished by humans. If I just want the model to classify all these sounds as "Siren" sound only. What... |
H: Measure of Separation for fuzzy clustering
Is there a measure of separation such as the Sillohete score for fuzzy clustering? I understand the logic for Hard-clustering algorithms but not sure about fuzzy. Is there a Python package for that such as scikit-learn?
AI: Why not using classing distance measurement such ... |
H: Use of multiple models vs training a single model for multiple outputs
So let's say I have data with numerical variables A, B and C.
I believe that the value of A has an effect on B.
I also believe that A and B both have an effect on C.
I don't think C has an effect on either A or B.
I want to use machine learning ... |
H: SAS Studio seems to imply that apparently non-normal data is normal
I have some data I'm trying to analyze in SAS Studio (university edition). I am using the Distribution Analysis feature to try to test some data for normality.
It gives me the following histogram:
Skewness is approximately 2.934 and Kurtosis is ap... |
H: Why checking the distribution of data is needed before calculating Gower distance?
I read this article(Clustering datasets having both numerical and categorical variables) to learn how to perform clustering on datasets with not just numerical variables.
Before calculating the Gower distance, distribution of data a... |
H: ValueError: Input 0 of layer sequential_7 is incompatible with the layer
I have 77 columns, with 4 class labels (already one-hot-encoded) by get_dummies.
x_train = X_train.reshape(-1, 1, 77)
x_test = X_test.reshape(-1, 1, 77)
y_train = y.reshape(-1, 1, 4)
y_test = y_test.reshape(-1, 1, 4)
batch_size = 32
model = ... |
H: Attention transformation - matrices
Could somebody explain which matrix dimension should be found here - K? and if it is for example 3X3, should I use just 9?
AI: $d_k$ is the dimensionality of the query/key/value vectors. In your example, the length of those vectors is 3, so $d_k = 3$ |
H: Random forest and the number of samples
I am new to AI and ML and I am learning how does random forest work. I implemented a small experiment. I have got a dataset with 1.6M samples and about 120 features. It is a classification problem, the output, which I am trying to predict, is a binary value. I am using Random... |
H: What is the scope of Keras' ImageDataGenerator.flow_from_dataframe seed parameter?
I've been working on a U-Net model using training images stored on my local drive. To load these I have been using Keras' ImageDataGenerator.flow_from_dataframe method and optionally applying some augmentations.
I have had no problem... |
H: Types Of Plots for Discrete Data
So I have a lot of discrete variables in my dataset and want to visualize them (univariate for now). I went through various articles over the internet and it is suggested that histograms and count plots are apt choices for plotting discrete data. Many of the discrete variables in my... |
H: Training a YOLO-style object detector
tl;dr I'm trying to train a small CNN (two conv layers and two connected layers) to find humans in the COCO dataset. Is my network big enough, and if so, roughly how many epochs of training will it need (there are 64115 training images)?
I am trying to make a neural network tha... |
H: Yolov3 Tiny: What do each of the 2535 cells detect?
Source: https://towardsdatascience.com/yolo-v3-object-detection-53fb7d3bfe6b
According to this image, it says the red grid is responsible for detecting the dog.
Similarly, do other cells detect "dog" as well or only the center ones?
For example, what do you think... |
H: What is fully connected layer additive bias?
I'm going to use PyTorch specifically but I suspect my question applies to deep learning & CNNs in general therefore I choose to post it here.
Starting at this point in this video and subsequently:
https://www.youtube.com/watch?v=JRlyw6LO5qo&t=1370s
George H. explains th... |
H: Normalize data between 0 and 95 instead of between 0 and 100
I want to normalize the data between 0 and 95 instead of 0 and 100. I am using this formula to normalize between 0 and 100, please let me know how to edit it.
def normalization(data):
return(data - np.min(data)) / (np.max(data) - np.min(data))
AI: Jus... |
H: Should I normalise my data if future unseen data may have a different range?
I'm new to ML and researching data prep, more specifically feature normalisation.
My question is whether it's a good idea to normalise data when its range may change over time?
For example, if I'm trying to predict stock prices in my train... |
H: relaying on feature during training that won't (necessarily) be available during prediction
I'm doing a little project of bugs prediction. My goal is to predict which bug will be (eventually) assigned to which relevant group (this is my label obviously).
For training, I'm relaying on a bugs database where I'm extra... |
H: Why it is recommended to use T SNE to reduce to 2-3 dims and not higher dim?
According to wiki it is recommenced to use T-SNE to map to 2-3 dimensional.
I can understand this , if we want to visualizing the data.
If we want to reduce the number of features (i.e from 30 features to 5 dims), is it recommended to do ... |
H: T-SNE with high number of features
If we have high number of features (more than 50), should we use T-SNE ?
According to https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html:
It is highly recommended to use another dimensionality reduction method (e.g. PCA for dense data or TruncatedSVD fo... |
H: What is the entity of cross entropy (loss)
Cross-entropy (loss), $-\sum y_i\;\log(\hat{p_i})$, estimates the amount of information needed to encode $y$ using Huffman encoding based on the estimated probabilities $\hat{p}$. Therefore one could claim it should be considered to measure the amount of information, for e... |
H: Is Cross validation and GridSearchCV required every time we train a model?
I have a repetitive process that will build a model weekly based on the previous week's data. So while in development I tried GridSearchCV and cross-validation to find the best hyperparameters and validate my model. Is this flow required eve... |
H: MOOC - for causal analysis - no statistics background
Am a software guy with no background in causal inference.
While I am now familiar with prediction techniques due to the plethora of courses available online, I would like to seek recommendations from people here for causal inference.
As you might know, how predi... |
H: How to convert float type nan in a dictionary value to 0.50?
I have a dictionary as below:
{
'$175000-199999': nan,
'$698506': nan
}
I want to convert the nan to 0.50. I tried using dictionary comprehensions
{k:v is 0.50 if v == nan else v for (k, v) in dictionary.items()} but it throws an error saying nan i... |
H: Evaluation metric for time-series anomaly detection
I have a question for AI or data experts. I'm writing a paper
My dataset are time-series sensor data and anomaly ratio is between 5% and 6%
1.
For time-series anomaly detection evaluation, which one is better, precision/recall/F1 or ROC-AUC ?
When empirically stud... |
H: Label data set for sentiment analysis
I am a beginner in this field. I have a scrapped review data set. It contains review socre (1 - 10) and review content. I am going to label the reviews according to the review score like below :
0-2 -> negative, 3-6 -> neutral, 7-10 -> positive
Is it possible to directly label ... |
H: How to obtain Accuracy of Feature Selection methods?
I used the following methods:
Variance_Threshold: selecto_vth = VarianceThreshold(threshold=1.0)
ANOVA: anova = SelectKBest(score_func=f_classif, k=20)
Mutual_Information: fs_mutual = SelectKBest(score_func=mutual_info_classif, k=20)
Sequential_Feature_Selector: ... |
H: How to structure unstructured data
I am analysing tweets and have collected them in an unstructured format. What is the best way to structure this data so I can begin the data mining processes?
Somebody suggested using python packages such as spacy but not sure how to go about using this.
AI: In Natural Language Pr... |
H: GridSearchCV and time complexity
So, I was learning and trying to implement a GridSearch. I have a question regarding the following code, which I wrote:
from sklearn.metrics import make_scorer
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import GridSearchCV
dtc = DecisionTreeClassif... |
H: Question regarding weights in a Model
Let's take a Linear regression model.I just want to know are weights the same for every row once the model is trained? Or are weights vector or an array for eg I have data X= [4,5] four rows and 5 features will the weights W be the same for every row or it is has a different va... |
H: Tips for clustering rows of a gigantic "distance" matrix
I've been assigned to the following task:
I was given 1,000,000 data points and was asked to create a sort of distance matrix and to cluster the rows.
So this matrix is 1,000,000 x 1,000,000 which is obviously way to large to fit on my poor 8GB of RAM.
I'd li... |
H: Memorization in deep neural networks, random vs. properly labelled datasets
From about 19:20 in the video here: https://www.youtube.com/watch?v=IHZwWFHWa-w
it shows the difference in value of the cost function for randomly labelled data vs. properly labelled data.
What do they mean by randomly labelled? That the l... |
H: Studying and choosing between different neural network structures
I would like to develop a model that uses convolutional neural networks for image classification. From the many different network structures described in papers and articles online, I would like to choose, as a starting point, the one that better sui... |
H: Training & Test feature shape is different from number of columns in dataset
I am making a Sequential Neural Network for regression with 3 dense layers which will be trained on a simple dataset. But before I even get to that part of the code to execute the model I am getting a different shape of my features than co... |
H: Visualization suggestion:-
I have a data frame like below:-
Here I have 194 countries and the columns are fan_out values which is in percent of the total population.
Like for country AD, the total fan_out value is 2.24 -06 % of the total population.
I tried a stacked chart like below:-
The only issue is it's not p... |
H: Overfitting in active learning
How can I make sure that the initial model trained on a small dataset will not suffer from overfitting before applying the active learning sampling techniques? because I will use this model to select new unlabeled samples.
AI: I'm not totally sure about my answer so please take it w... |
H: can't understand the Architecture of Neural Network
Please explain how Z1 is working I just want to know why W is of shape (4,3) I understand that there are four Weights we are performing (4,3)*(3,1) + (4,1) but I don't understand what is 3 in (4,3)
Just write the full equation of Z1 rest is self-explanatory.
I N... |
H: Plot NaNs as a category seaborn countplot
I have a column in my dataframe which has 'True' as a value and all other values are NaNs (so there are no 'false' values). I want to plot a countplot for the said data in seaborn but want to include the NaNs as well. Basically, I want to convert the NaNs to 'false' values ... |
H: Does it means a high accuracy of model will have high confidence score
I am trying to select a model from different CNN trained models based on some parameter.
Initially, I was considering using model confidence score to decide which model is better. Now I am considering using accuracy for the selection of a good m... |
H: What is the disadvantage of using a completely normalized training set for Deep learning?
Batch normalization is generally preferred in deep learning, which normalizes the output of the activation function in each layer (as an output from the cost function differs depends on the input).
Instead, if the training set... |
H: Returning a DataFrama with nlargest values based on a particular column
This is my sample DataFrame:
inputArr = [['A', 0, 6],
['A', 1, 57],
['A', 2, 81],
['A', 3, 9],
['A', 4, 87],
['B', 0, 24],
['B', 1, 30],
['B', 2, 96],
['B', 3, 54],
['B', 4, 81],
['C', 0, 6],
['C', 1, 6],
['C', 2, 6],
['C', 3, 93],... |
H: What is difference between Validation steps and Steps per epoch?
I am trying to understand the difference between validation steps and steps per epoch, Can anybody tell me the difference between these two terms. I also want to know about, how will it be helpful in training and what number should we set in it?
AI: V... |
H: Cosine vs Manhattan for Text Similarity
I'm storing sentences in Elasticsearch as dense_vector field and used BERT for the embedding so each vector is 768 dim. Elasticsearch gives similarity function options like Euclidean, Manhattan and cosine similarity. I have tried them and both Manhattan and cosine gives me ve... |
H: Identifying problematic binary features in classification task
I am working on a classification problem consisting of data with binary features. I am trying to find which features, when equal to 1 give a false negative for a particular class.
To better illustrate my point consider the data below consisting of sampl... |
H: Efficient way to tackle card games with many q-table states?
I'm currently in the process of developing an AI for a popular card game here in Germany (called "Schafkopf"). Obviously, one could try to find a perfect strategy with the help of some game theory, but I tried the path with ML. Now after implementing the ... |
H: Input to `.fit()` should have rank 4. Got array with shape: (31500, 784)
I am new to CNNs and am working on/using the MNIST dataset. After splitting the data to train and test sets, I needed to use 'ImageDataGenerator'. The code I used is the same code on the Keras API site.
The shapes are as below:
print(X_train.s... |
H: Given M binary variables and R samples, what is the maximum number of leaves in a decision tree?
Given M binary variables and R samples, what is the maximum number of leaves in a decision tree?
My first assumption was that the worst case would be a leaf for each sample, thus R leaves maximum. Am I wrong and there s... |
H: Really confused with characteristics of Naive Bayes classifiers?
Naive Bayes classifiers have the following characteristics-:
They are robust to isolated noise points because such points are
averaged out when estimating contiditional probabilities from data.
Naive Bayes classifiers can also handle missing values ... |
H: Alternative to EC2 for running ML batch training jobs on AWS
We are building an ML pipeline on AWS, which will obviously require some heavy-compute components including preprocessing and batch training.
Most the the pipeline is on Lambda, but Lambda is known to have time limits on how long a job can be run (~15mins... |
H: What is the benefit of training an ML model with an AWS SageMaker Estimator?
It looks like there are different routes to deploying an ML model on SageMaker. You can:
pre-train a model, create a deployment archive, then deploy
create an estimator, train the model on SageMaker with a script, then
deploy
My questi... |
H: Are there any popular English corpus?
Are there any popular English corpus?
AI: Finding corpora for NLP research can be hit and miss, my advice would be to study the availability of adequate data when deciding about the research direction, not afterwards. Of course this completely depends on the type of requirement... |
H: What does bootstrap mean in scikit-learn's BaggingClassifier?
I just started using scikit-learn and was learning about the BaggingClassifier. I am a little confused on what bootstrap means. The meaning on the scikit-learn website doesn't make sense. Just asking for a little help. Thanks.
AI: Bootstrapping methods r... |
H: Reducing The Impact of Luck On My Training Data
I am new to this data science stuff and I am trying a project on my own to learn more about this field. So I have a project that has the goal of taking in a bunch of features and indicating whether a player will make or miss a shot.
My current training data has a bunc... |
H: Different values of mean absolute error when using GridSearchCV for max_leaf_nodes vs manually optimising max_leaf_nodes
I am trying out hyperparameter tuning vs manually selecting the best parameter (max_leaf_nodes) on a decision tree model with mean absolute error as the scoring. In theory, both should give me ... |
H: Gamma parameter in xgboost
As per the original paper on xgboost, the best split at a node is found by maximising the quantity below
$
\cal{L}_{\rm split} = \frac{1}{2} \sum \left [ \frac{G_L}{H_L + \lambda} + \frac{G_R}{H_R + \lambda} - \frac{G_I}{H_I + \lambda} \right ] - \gamma
$
There exists a gamma parameter i... |
H: Traditional alternatives to Caputure Words Sequence information in NLP
What were the traditional/earlier methods in which NLP researchers captured the word sequence information through feature engineering?
I know the current methods which rely on deep learning models like roBERT and BERT and work well with capturin... |
H: What is the difference between BERT and Roberta
I want to understand the difference between BERT and Roberta. I saw the article below.
https://towardsdatascience.com/bert-roberta-distilbert-xlnet-which-one-to-use-3d5ab82ba5f8
It mentions that Roberta was trained on 10x more data but I don't understand the dynamic m... |
H: Choosing a Change Point Detection Algorithm
I am currently working on a dataset that belongs to the restaurant and food delivery domain. After completing sentiment analysis and quantification, I now need to select a Change Point Detection Algorithm and detect a shift in the sentiment signal in the reviews on each c... |
H: How does Word2Vec actually help with sentimental analysis?
I'm trying read in a whole article, separate the article by sentences, and then words. Then I pass this into the Word2vec Model and the output comes out.
However, my goal is to find the positive or negative sentiment of the article. The input is unsupervise... |
H: How is there an inverse relation between precision and recall?
What I know?
Firstly,
Precision= $\frac{TP}{TP+FP}$
Recall=$\frac{TP}{TP+FN}$
What book says?
A model that declares every record has high recall but low precision.
I understand that if predicted positive is high, precision will be low. But how will re... |
H: what can be done using NLP for a small sentence samples?
I am new to NLP. I have few 100 textual sentences (100 rows in dataframe) with an average word length of 10 in a sentence. I would like to know what interesting insights (simple descriptive to advanced) can be derived using NLP techniques. I don't intend to p... |
H: Implementing computational graph and autograd for tensor and matrix
I am trying to implement a very simple deep learning framework like PyTorch in order to get a better understanding of computational graphs and automatic differentiation. I implemented an automatic differentiator for scalar values inspired by this a... |
H: Loss is Nan even with clipvalue set and Adam optimizer
I'm currently doing this task from kaggle.
I've normalized my data with the minmax scaler and fixed the dummie variable trap by removing one column to every dummie variable I created.
Here is the first row of my training data:
array([0.45822785, 0.41137515, 0.4... |
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