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H: How to use BERT in seq2seq model?
I would like to use pretrained BERT as encoder of transformer model. The decoder has the same vocabulary as encoder and I am going to use shared embeddings. But I need <SOS>, <EOS> tokens which are not trained with BERT. How should I get them ? Can I use <CLS> token as <SOS> and <S... |
H: Choosing best model produced from different algorithms. Metric produced by cross-validation on the train set or metric produced on the test set?
I know that choosing between models produced by one algorithm with different hyperparameters the metric for choosing the best one should be the cross-validation on train s... |
H: Regression and Classification in one Neural network
For example consider object localization problem. Here NN will have 5 ouputs. output[0] will tell probability of object present in image, other 4 will tell bounding box coordinates.
As we see that output[0] has to use classification loss like cross entropy and out... |
H: Are Deep Neural Networks limited to grayscale images depending on whether you use Seq. or Func. API?
When I say DNN, I mean the simple usage of densely connected neurons (not CNN).
Say we are using Keras (with Tensorflow backend), the input_dim, using the Sequential API, can only take an integer or None value which... |
H: Pros and Cons of Positive Unlabeled learning?
I've been looking for papers that discuss the pros and cons of positive unlabeled learning but I haven't been able to find anything.
I'm looking to compare the general differences between creating a positive-unlabeled based problem vs a regression classification. I have... |
H: DIGITS Docker container not picking up GPU
I am running DIGITS Docker container but for some reason it fails to recognize host's GPU: it does not report any GPUs (where I expect 1 to be reported) so in the upper right corner of the DIGITS home page there is no indication of any GPUs and also during the training pha... |
H: ImportError: Pandas requires version '0.3.0' or newer of 's3fs'
I'm trying to read files from S3, using boto3, pandas, anaconda, but I have the following error:
ImportError: Pandas requires version '0.3.0' or newer of 's3fs'
(version '0.1.6' currently installed).
How can I update the s3fs version?
This is my code... |
H: What is the difference between Okapi bm25 and NMSLIB?
I was trying to make a search system and then I got to know about Okapi bm25 which is a ranking function like tf-idf. You can make an index of your corpus and later retrieve documents similar to your query.
I imported a python library rank_bm25 and created a sea... |
H: Learning Curves and interpretations
I've trained 4 classifiers on an undersampled dataset.
I plotted the learning curve for each classifier and I got the following results :
I see that for the Log Reg, both curves seem to converge and that adding more data will not help at some point.
For the SVC I have no idea (r... |
H: ImportError: cannot import name 'cv2' from 'cv2'
I'm using anaconda and installed OpenCV using conda-forge.
conda install -c conda-forge opencv
In my notebook I run this line of code
from cv2 import cv2
Unfortunately, get this error message:
ImportError: cannot import name 'cv2' from 'cv2' (C:\Users\...\Anaconda3\... |
H: What is the best practice for tuning hyperparameters using validation data?
I'm building a binary classifier, using task-transfer from resnet and a total training set of 300 images.
Initially I put aside 100 images as validation, and tuned the hyperparameters, each time training on 200 and testing on 100, until I g... |
H: Confusion about the Bellman Equation
In some resources, the belman equation is shown as below:
$v_{\pi}(s) = \sum\limits_{a}\pi(a|s)\sum\limits_{s',r}p(s',r|s,a)\big[r+\gamma v_{\pi}(s')\big] $
The thing that I confused is that, the $\pi$ and $p$ parts at the right hand side.
Since the probability part - $p(s',r... |
H: How to use inverse_transform in MinMaxScaler for pred answer in a matrix
I am working on a data, for preding output, I used SVR by bellow code:
from sklearn.svm import SVR
regressor = SVR(kernel = 'linear')
regressor.fit(trainX,trainY)
from sklearn.metrics import r2_score
pred = regressor.predict(testX)
print(pred... |
H: Learning rate of 0 still changes weights in Keras
I just trained a model (SGD) with keras and was wondering why the change of accuracy and loss from epoch to epoch doesn't really decrease that much when I lower the learning rate. So I tested what happens when I set the learning rate to 0 and to my surprise, accurac... |
H: Performing anomalie detection on a battery volatge using LSTM-RNN
I am trying to detect anomalies in a battery output voltage for one month.
I have the next data frame, as it is shown the data is collected each minute for each day so I have almost 1420 sample per day.
Should I use the 'time' or the 'date' column i... |
H: How to decrease $R^2$ value and change it to positive value
I'm working on a data, and use regression , as you see bellow:
from sklearn.svm import SVR
regressor = SVR(kernel = 'linear')
regressor.fit(trainX,trainY)
above answer is:
SVR(C=1.0, cache_size=200, coef0=0.0, degree=3, epsilon=0.1, gamma='scale',
ker... |
H: What is the difference between spiral, flame, aggregation data
What is the difference between spiral, flame, aggregation data? What are the names of the columns, or what are the columns indicate?
For example, spiral is like to:
31.95 7.95 3
31.15 7.3 3
30.45 6.65 3
29.7 6 3
28.9 5.55 ... |
H: Is there any different between feature selection and pca? If there is could anyone please kindly explain for me please?
First of sorry for asking a possibly beginner question, but i don't understand pca seems to be the same as feature selection, but when i search online they seems to be talked differently. What peo... |
H: Why are mBART50 language codes in an unusual format?
I am trying to use mBART for multilingual translation(about 30 languages) but I am facing an issue with using it as I am currently using langid to identify the languages then load mBART and translate all the words based on the language code that has been identifi... |
H: Multiplying a dataframe by a larger one
I have two dataframes df1 and df2 with the same columns but not the same row number.
I want to multiply them element-wise such that the smallest one (df1) fits into the first corresponding rows of the largest one (df2), and gives 0 for the remaining cells. I tried df1.mul(df2... |
H: Keras/Tensorflow: model.predict() returns a list. How do I match the output with my class names?
I have a CNN built in Keras. I have saved it and am now using the model.predict() function to make predictions from it. Whenever I run the following code,
def prediction(path):
import keras
from keras.preprocess... |
H: IterativeImputer Evaluation
I am having a hard time evaluating my model of imputation.
I used an iterative imputer model to fill in the missing values in all four columns.
For the model on the iterative imputer, I am using a Random forest model, here is my code for imputing:
imp_mean = IterativeImputer(estimator=Ra... |
H: Why does my manual derivative of Layer Normalization imply no gradient flow?
I recently tried computing the derivative of the layer norm function (https://arxiv.org/abs/1607.06450), an essential component of transformers, but the result suggests that no gradient flows through the operation, which can't be true.
Her... |
H: Is it good practice to transform some variables and not others?
I have a dataset with categorical variables encoded into numeric values, other variables that are continuous and have many outliers, and other continuous variable with a fairly normal distribution.
I was planning to use the sklearn preprocessing method... |
H: XLNET how to deal with text with more than 512 tokens?
From what I searched online, XLNET model is pre-trained with 512 tokens, and https://github.com/zihangdai/xlnet/issues/80 , I didn't find too much useful information on that either.
How does XLnet outperform BERT on long text when the max_sequence_length hyperp... |
H: What is different between R2 and mean of R2 in multiclassification probelm? Which one is correct?
I have a question. I have a big dataset (unfortunately confidential).
What I did?
I have trained my model with Naive-Bayes.
BRNBReg=BernoulliNB(alpha=0.01, binarize=0.0, fit_prior=True, class_prior=None)
BRNBReg.fit(x_... |
H: Neural network type question
This web link is to a site that talks about forecasting building electricity, like a time series regression concept.
In the article they talk about the NN architecture as:
the architecture of this neural network can be written as 120:7:24
Is an MLP type NN? What I also dont understand... |
H: How to use GridSearch for LinearSVC / Random Forest with time series data
I have a question related on how to use the GridSearch to find the best models for my problem with time series data.
Every 3 rows is 1 one row in the original dataset. To make my time series problem a supervised one, I parsed like the one bel... |
H: Conv1D layer input and output
Consider the following code for Conv1D layer
# The inputs are 128-length vectors with 10 timesteps, and the batch size
# is 4.
input_shape = (4, 10, 128)
x = tf.random.normal(input_shape)
y = tf.keras.layers.Conv1D(32, 3, activation='relu',input_shape=input_shape[1:])(x)
print(y.sh... |
H: How can I preprocess text to feed into a SVM?
I am using an IMDB dataset which contains reviews of the movies in the column text and the rating 0 or 1 in the column label. I am preprocessing the text using Tfidf using sklearn.
The code for the above statement
from sklearn.feature_extraction.text import TfidfVectori... |
H: Statsmodel logit with sample weights
Using sklearn I can consider sample weights in my model, like this:
from sklearn.linear_model import LogisticRegression
logreg = LogisticRegression(solver='liblinear')
logreg.fit(X_train, y_train, sample_weight=w_train)
Is there some clever way to consider sample weights also i... |
H: cost-complexity-pruning-path with pipeline
I'm using Kaggle's titanic set. I'm using pieplines and I'm trying to prune my decision tree and for that I want the cost_complexity_pruning_path. The last line of code produces the error:
ValueError: could not convert string to float: 'male'
Do you know what I'm doin... |
H: How match output (pred value) to input value
I'm working with data(with 4 columns which are p(product), M(name of the store)), I want predict the demand of store for that I sued SVR on the data by theses formulation:
dfn = pd.get_dummies(df)
x = dfn.drop(["demand"],axis=1)
y = dfn.demand
from sklearn.preprocessing ... |
H: Normalized 2D tensor values are not in range 0-1
Below function takes in 2D tensor and normalizes it using broadcasting .The issue is except all values to be in range 0-1 but the result has values outside this range . How to get all values in 2D tensor in range 0-1
def torch_normalize(tensor_list):
means = tens... |
H: Classification Threshold Tuning with GridSearchCV
In Scikit-learn, GridSearchCV can be used to validate a model against a grid of parameters. A short example for grid-search cv against some of DecisionTreeClassifier parameters is given as follows:
model = DecisionTreeClassifier()
params = [{'criterion':["gini","ent... |
H: Intuitive explanation of Adversarial machine learning
How would you explain Adversarial machine learning in simple layman terms for a non-STEM person? What are the main ideas behind Adversarial machine learning?
AI: Consider a game being played between two people, for simplicity, we'll assume this game is distingui... |
H: Metric for label imbalance
I'm looking for a metric that can be used to quantify how imbalanced the labels are in a dataset.
I'm not looking for a strategy to solve the imbalance problem, I just want to present how imbalanced my dataset is. I've computed the ratio of the most frequent and least frequent labels whic... |
H: LinearRegression with fixed slope parameter
I have some data $(x_{1},y_{1}), (x_{2},y_{2}), ..., (x_{n},y_{n})$, where both $x$ and $y$ represent real numbers (float). I want use Scikit-learns LinearRegression model to fit a model of the form:
$y_{i} = b_{0} + b_{1}x_i + e_{i} $
Typically, I know that OLS is used t... |
H: Interpretation of Autocorrelation plot
I am trying to understand better how to read the autocorrelation plot here for a timeseries data.
I ran the following code and got the output as a chart show below.
from pandas.plotting import autocorrelation_plot
autocorrelation_plot(df("y"))
Here y is the dependent variable... |
H: Multiple Regression, Classification and Boundary Poins
I have two gangs which are doing crimes. And i want to classify them.
Lets say I'm looking for a regression function:
M(x1, x2) = w1x1 + w2x2 + w3
Now I have found all three parameters w1, w2, w3.
Now I want to do classification. I get some boundary points ... |
H: What is the opposite of baseline?
I have created a prediction model and on the one hand I have to compare it with other baseline models, and on the other hand, I have to compare it with the ideal approach (supported by additional data), so I would like to know how I can call it (antonym of baseline) in the research... |
H: What is the advantage of a tensorflow.data.Dataset over a tensorflow.Tensor?
I have my own input data class. It has x and y as well as test and train values (1 Tensor for each combination). I noticed there is a Dataset class built in to TensorFlow. What is the advantage of this class over a regular Tensor? Is it ma... |
H: Validation loss diverging away from the training loss
I used the XLNET for a sentiment classifier in determining whether a comment is positive or negative. I was able to get good results
But when I plotted the validation and training losses I saw this
I think this means that the model is overfitting? But I am not... |
H: How to specify output_shape parameter in Lambda layer in Keras
I don't understand how to specify the output_shape parameter in the Lambda layer in Keras/Tensorflow. The documentation says:
output_shape: Expected output shape from function. This argument can
be
inferred if not explicitly provided. Can be a tuple or... |
H: is this problem a multiclass case?
I'm trying to classify my textile design patterns
(let's just think of it as medieval painting)
what I understand of "multilabel classification" is like this:
it outputs multiple possible result out of all those classes (let's say classes are of some artists, style and technique)
... |
H: How does the equation "dW = - (2 * (X^T ).dot(Y - Y_hat)) / m" comes in Linear Regression (using Matrix + Gradient Descent)?
I was trying to code the Linear Regression in Python using Matrix Multiplication method using Gradient Descent and followed a code where there was no mention what is the loss but just a code ... |
H: How to interpret training and testing accuracy which are almost the same?
Note - I have read this post but still don't understand
I have a Naive Bayes classifier, when I input my training data to test the accuracy, I get 63.05%. When I input my test data, the accuracy is 65.00%.
Why are the training and test accura... |
H: Heat map and correlation among variables
I would have a question on heat map and correlation among variables.
I created this heat map, looking at possible correlation among variables and target. I got very small values.
I wanted to set a small threshold, e.g., 0.05, for selecting features.
Do you think it makes sen... |
H: Looking for binary class datasets with high class imbalance, that also have intra-class imbalance in the minority class
Newbie question alert...
For a college project I want to compare a few variants of SMOTE in terms of how much they improve classification of the minority class, over using random oversampling.
I h... |
H: mean and variance of a dataset
I have a simple question. Please see the below screenshot :
It is from a midterm exam from a university : https://cedar.buffalo.edu/~srihari/CSE555/exams/midterm-solution-2006.pdf
My questions is how the means are postive ? I am asking because the class samples are all negative so I ... |
H: Quick question on basic Basic concept of experience replay
Due to my admitted newbie's understanding on the field, I'm about to ask a dummy question.
While sampling batches, for example experience replay buffer which contains number of samples, after getting n (size of a batch) of loss values through forward propag... |
H: Difference between zero-padding and character-padding in Recurrent Neural Networks
For RNN's to work efficiently we vectorize the problem which results in an input matrix of shape
(m, max_seq_len)
where m is the number of examples, e.g. sentences, and max_seq_len is the maximum length that a sentence can have... |
H: How can i increase the memory of Jupyter?
What I have:
I have a data set (35989 rows × 16109 columns) and is unfortunately confidential.
But i receive this error massage:
Unable to allocate 4.32 GiB for an array with shape (16109, 35994) and data type float64
How can i solve this problem?
AI: Assuming you cannot a... |
H: Changing order of LabelEncoder() result
Assume I have a multi-class classification task. The labels are:
Class 1
Class 2
Class 3
After LabelEncoder(), the labels are transformed into 0-1-2.
My questions are:
Do the labels have to start from 0?
Do the labels have to be sequential?
What happens if I replace all la... |
H: RF regressor for probabilites
I am using sklearn multioutput RF regressor to learn statistics in my data. So my target contains several probabilities for the different features, and the sum of all these probabilities is one as they are fractions of how often the feature occurs.
The RF actually learns this property ... |
H: What is the input of LSTM network?
Hello I am trying to understand LSTMs but have a few problems:
What is the input? Since LSTM is seq2seq I would think it is a sequence of words, but in a Codecademy lesson is mentioned that each sentence is represented as a matrix with a bunch of vectors containing 1 or 0 for the... |
H: How to select the best parameters for GridSearchCV?
I've created a couple of models during some assignments and hackathons using algorithms such as Random Forest and XGBoost and used GridSearchCV to find the best combination of parameters. But what I'm not able to understand is how to select those parameters for Gr... |
H: How to run a saved tensorflow model in the browser?
After doing my hello world models, I would like to let them available at Github pages, which means that I need to serve the model only with static files. Is it possible?
All the tutorials I found requires nodejs or some backend
AI: You can find exactly that at thi... |
H: LDA topic model has 0-weight topics, is that normal?
While experimenting with different number of topics for the Gensim implementation of LDA, I found that for a high number of topics, the output often consists of topics with all weights equal to zero. Is this an indication of an implementation mistake or is this n... |
H: Function growing faster for negative inputs than for positives
I am working on a regression problem where I want to model the loss function in a way that it "punishes" to big errors much more than small errors (so I am in the realm of exponential functions) but also in a way that is punishes a negative error much m... |
H: Replace part column value with value from another column of same dataframe
I have a dataframe with two columns:
Name DATE
Name1 20200126
Name2 20200127
Name#DATE# 20200210
I need to replace all the #DATE# with the data from the DATE column, and get something like this:
Name
Na... |
H: Extracting Names using NER | Spacy
I'm new to NER and I've been trying to extract names using Spacy. Here's my code:
import spacy
spacy_nlp = spacy.load('en_core_web_sm')
doc = spacy_nlp(text.strip())
# create sets to hold words
named_entities = set()
money_entities = set()
organization_entities = set()
location... |
H: Tricky stacking models in keras
I'm trying to write a model with keras, that is built as shown below:
| +-----+
+->+------+ | |
+--->| NN |------>| |
| +------+ | |
| | | |
| +->+------+ | |
+--->| NN |------>| L |
| +------+ ... |
H: Comparing ML models to baselines
When comparing ML models with baseline or "dummy" models, are there best practices for building and comparing baselines?
I'm doing a binary classification task where 40% of the samples are class_0 (untreated class), and the other 60% are class_1 (treated/positive class).
I have two ... |
H: Approach for training multilingual NER
I am working on multilingual (English, Arabic, Chinese) NER and I met a problem: how to tokenize data?
My train data provides sentence and list of spans for each named entity.
e.g.
[('The', 'DT'),
('company', 'NN'),
('said', 'VBD'),
('it', 'PRP'),
('believes', 'VBZ'),
('... |
H: What if My Word is not in Bert model vocabulary?
I am doing NER using Bert Model. I have encountered some words in my datasets which is not a part of bert vocabulary and i am getting the same error while converting words to ids. Can someone help me in this?
Below is the code i am using for bert.
df = pd.read_csv("d... |
H: Could you generate search queries to poison data analysis by a search engine?
A simple problem with search engines is that you have to trust that they will not build a profile of search queries you submit. (Without Tor or e.g. homomorphic encryption, that is.)
Suppose we put together a search engine server with a u... |
H: Decoder Transformer feedforward
I have a question about the decoder transformer feed forward during training.
Let's pick an example: input data "i love the sun" traduction i want to predict (italian traduction) "io amo il sole".
Now i feed the encoder with the input "i love the sun" and i get the hidden states.
Now... |
H: Vertical concatenation in a df based on column value_python
Is there any way to concatenate vertically a specific column from my df (concat1), considering/filtering values from another column (col_value)?
My df looks like this:
col_value concat1
data1 x;y;z
data1 d;f;h
data1 ... |
H: Calculating correlation for categorical variables
I am struggling to find out a suitable way to calculate correlation coefficient for categorical variables. Pearson's coefficient is not supported for categorical features. I want to find out features with most highest influence on the target variable. My objectives ... |
H: Problem with binning
I am trying to change continuous data points to categorical by using binning. I know two techniques, i) equal width bins ii) bins with equal number of elements.
My questions are:
Which type of binning is appropriate for which kind of problem?
I use pandas for my data analysis task and it has p... |
H: Read csv file and save images from the output
I have created some code that reads my CSV file and converts the dataset to a grayscale image. I want to know if there is any possible way to read through each row in the dataset and save each of the images created from the rows?
So far, I have got this code that reads ... |
H: Very bad results for input-output mapping using an Artifical Neural Network
I'd like to hear the opinion of an expert for artifical neural networks on a problem that I try to solve. I just started to use articial neural networks and want to train an ANN with 3 inputs and 3 outputs by using 3375 data points. The goa... |
H: How to interpret the Mean squared error value in a regression model?
I'm working on a simple linear regression model to predict 'Label' based on 'feature'. The two variables seems to be highly correlate corr=0.99. After splitting the data sample for to training and testing sets. I make predictions and evaluate the ... |
H: Using user defined function in groupby
I am trying to use the groupby functionality in order to do the following given this example dataframe:
dates = ['2020-03-01','2020-03-01','2020-03-01','2020-03-01','2020-03-01',
'2020-03-10','2020-03-10','2020-03-10','2020-03-10','2020-03-10']
values = [1,2,3,4,5,10,2... |
H: Implementing the Trapezoid rule without the formula for the curve
I know that if I have some function f(x) that describes a curve, I can approximate the area under the curve using the trapezoid rule as follows:
def auc(f, a, b, n):
subinterval = (b - a) / n
s = f(a) + f(b)
i = 1
while ... |
H: Are there readily available models that can handle conditional correlation?
I've been working my way through the features of the Kaggle House Prices dataset (Note: this is a non-ranking entry, so this is just for exercises), and I've found a couple situations where there is a positive correlation between the featur... |
H: What's the best way to generate similar words?
Hi all I'm fairly up to date with all the NLP tasks out there (nlpprogress.com, paperswithcode.com) and great tools like (nltk, flair, huggingface etc). I want to take a single word, and predict a similar word, a little like the old "Google Sets" feature except extrapo... |
H: How does the Transformer predict n steps into the future?
I have barely been able to find an implementation of the Transformer (that is not bloated nor confusing), and the one that I've used as reference was the PyTorch implementation. However, the Pytorch implementation requires you to pass the input (src) and the... |
H: Do we need to do multiple times deep learning and average ROC?
Do we need to do multiple times deep learning and average ROC(AUC)?
Since we've might get different ROC(AUC) every round we train and test (by KERAS)
Is it necessary to average ROC(AUC) with multiple times training and testing?
(or just choose the best ... |
H: What is a "shot" in machine learning?
I keep on hearing this term "shot" used in machine learning.
Is a "shot" well-defined?
From what I can tell, "shot" is a synonym for "example". Most machine learning systems seem to be "multi-shot" meaning you have a huge dataset that has many different examples of different ca... |
H: Neural network: does bias equal to zero, is the same as, a layer without bias?
Question as in the title. Does bias equal to zero, is the same as, removing bias from the layer? Here's a pytorch implementation to showcase what I mean.
class MLP_without_bias(torch.nn.Module):
def __init__(self):
super().__... |
H: Is there potentially data leakage during imputation for time-varying sensor data?
I have a time-varying dataset that contains some missing data. I have sensors that continuously monitor some properties at evenly-spaced intervals and I would like to impute the missing values using basic interpolation for both the tr... |
H: Understanding features vs labels in a dataset
I am in the process of splitting a dataset into a train and test dataset. Before I start, this is all relatively new to me. So, from my understanding, a label is the output, and a feature is an input. My model will detect malware, and so my dataset is filled with malwar... |
H: How much imbalance in a training set is a problem?
In a simple binary classification problem, at what point does majority class to minority class become significant become significant? Intuitively, I would expect a 3:1 ratio to not be an issue, maybe not even a 10:1 ratio. But a 100:1 ratio certainly does require s... |
H: Extract key phrases for binary outcome
I have a set of phrases that lead to a binary outcome (accept/reject) and I was wondering what techniques are most helpful for extracting key phrases that are most likely to determine the outcome, given that I have a training set of data that has the English-language phrase an... |
H: Effect of removing duplicates on Random Forest Regression
I have a dataset with several million samples that have 5 features and 1 target, which I am using for a regression model. With very large sample counts some models (like Random Forests) become very large (several GB when pickled).
These data often have dupl... |
H: Imputing missing value based on filtering result of another column
C1
C2
A
x
A
y
A
z
A
x
A
NaN
A
x
A
x
A
x
B
y
B
y
B
z
B
y
B
NaN
B
y
B
x
B
x
I have to impute missing values in C2 , the imputation should be such that if the missing values corresponding C1 column is A, then f... |
H: What issue is there, when training this network with gradient descent?
Suppose we have the following fully connected network made of perceptrons with a sign function as the activation unit, what issue arises, when trying to train this network with gradient descent?
AI: what issue arises, when trying to train this n... |
H: Why do my target labels need to begin at 0 for sparse categorical cross entropy to work?
I'm following a guide here to implement image segmentation in Keras.
One thing I'm confused about are these lines:
# Ground truth labels are 1, 2, 3. Subtract one to make them 0, 1, 2:
y[j] -= 1
The ground truth targets are .p... |
H: How do you search for content, not words?
Given a string that describes a situation or method, are there algorithms that create fingerprints out of it, compare it with a corpus to then point to pages where a similiar concept is being discussed?
The simple form is word search.
You search for word X and X appears in ... |
H: Is my CNN model overfitting?
I'm training a standard CNN. Attached my training curve. My model:
Model: "functional_35"
_________________________________________________________________
Layer (type) Output Shape Param #
================================================================... |
H: Adjusting imbalance in classification problem reduce precision, accuracy but increase recall
I've learned that adjusting imbalanced data when training a CNN affects model performance which got me thinking "what about in ML?" so I've done some testing on my own, you can check it out here -> https://haneulkim.medium.... |
H: is it possible to decide model without any data?
Today I just faced a very unique demand from my superior. He asked me whether I can make a model first before we gather the data for training because we don't have any data yet.
I was utterly confused about what to do with this. Did anyone have any suggestion how sh... |
H: Implementing U-Net segmentation model without padding
I'm trying to implement the U-Net CNN as per the published paper here.
I've followed the paper architecture as closely as possible but I'm hitting an error when trying to carry out the first concatenation:
From the diagram, it appears the 8th Conv2D should be m... |
H: Has anyone heard of a model similar to a random forest which fits a linear regression model in its leaf nodes?
That is, each leaf node in each decision tree learns a linear model.
Anyone heard of this kind of model? Even better, anyone know of implementations?
AI: M5P Model Trees are the closest thing that I'm awar... |
H: Hot to use the formula model in t.test
I am trying to better understand the formula model for two sample t-tests in R. When I calculate the test in the formula model I get a wrong result.
set.seed(41)
df = data.frame(x1=c(rep(1, 10), rep(0, 10))+ rnorm(20, mean = 0, sd = 0.1),
x2=c(rep(0, 10), rep(1,... |
H: Resampling : My dataset is categorical or numerical?
I have a dataset with 203 variables. Like age>40 (0 -yes, 1-no), gender(0 or 1), used or not 200 types of drugs (one hot encoded into 200 variables), and one target variable (0 or 1). This is an imbalanced dataset where Counter({0: 5607, 1: 1717}).
May I know wha... |
H: Is feature importance from classification a good way to select features for clustering?
I have a large data set with many features (70). By doing preprocessing (removing features with too many missing values and those that are not correlated with the binary target variable) I have arrived at 15 features. I am now u... |
H: sklearn package with AttributeError: 'MissingValues' object has no attribute 'to_list'
I am currently trying to reproduce this tutorial on building a CNN based time series classifier for human activity recognition.
My setup is:
Windows 10, Pycharm IDE with a new project for this tutorial, Python3.6, freshly instal... |
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