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H: How to get model attributes in scikit learn (not hyper parameters)
How to get model attributes list (not hyper parameters passed to Estimator's class)?
For ex:
kmeans = KMeans(n_clusters=5)
kmeans.fit(X)
kmeans.labels_
how to get list of the attributes like labels_ from model object (ending with _)?
AI: I believ... |
H: Topics to learn in Neural Network
I have recently started learning Deep Neural Networks and was going through the tutorials online. Everywhere I saw that the topics post Image classification using CNN is a little hazy. No one seems to follow a guide as to what topics should one learn after learning image classifica... |
H: Time series binary classification
Which deep learning architecture and algorithms do you most recommend for time series classification problem?
Of course LSTM, I am looking for state of the art papers.
AI: https://paperswithcode.com/task/time-series-classification/latest -> You can find all the state-of-the-art pap... |
H: pandas groupby and sort values
I am studying for an exam and encountered this problem from past worksheets:
This is the data frame called 'contest' with granularity as each submission of question from each contestant in the math contest. The question is
and the answer is in red. I get why that works, but why is t... |
H: Selecting threshold for F1 Score
When selecting a probability threshold to maximize the F1 score prior to deploying a model (based on the precision-recall curve), should the threshold be selected based on the training or holdout dataset?
AI: Ideally, the threshold should be selected on your training set. Your holdo... |
H: Negatively correlated features
Is it ok to use negatively correlated features in data modeling? Say I have features A and B that have a correlation coefficient of 0.2 and features C and D with -0.2 correlation coefficient, is it fine to use features C and D in the model, since they have a low negative correlation? ... |
H: How to use df.groupby() to select and sum specific columns w/o pandas trimming total number of columns
I got Column1, Column2, Column3, Column4, Column5, Column6
I'd like to group Column1 and get the row sum of Column3,4 and 5
When I apply groupby() and get this that is correct but it's leaving out Column6:
df ... |
H: How is GPT able to handle large vocabularies?
From what I understand, GPT and GPT-2 are trained to predict the $N^{th}$ word in a sentence given the previous $N-1$ words. When the vocabulary size is very large (100k+ words) how is it able to generate any meaningful prediction? Shouldn't it become extremely difficul... |
H: First two principal components explain 100% variance of data set with 300 features
I am trying to do some analysis on my data set with PCA so I can effectively cluster it with kmeans.
My preprocessed data is tokenized, filtered (stopwords, punctuation, etc.), POS tagged, and lemmatized
I create a data set of about ... |
H: How to use id's in binary classification problem
I would like to predict for a given user (on a website) if he/she logs out from the website within ten minutes.
In terms of data, I have a user ID and timestamp of the latest post on the website.
example of an id: 54a47e7a9cd118513
It would be great to get advice on ... |
H: AttributeError: 'DataFrame' object has no attribute 'ix'
I was learning Classification-based collaboration system and while running the code I faced the error AttributeError: 'DataFrame' object has no attribute 'ix'. Here is the code I write until now.
X=bank_full.ix[:,(18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,... |
H: Confusion between precision and recall
I have a machine learning model that try to fingerprint the functions in a binary file with a corpus. Final output of upon inputing a binary file is a table with one to one mapping between the binary function and the corpus function as follows-:
As you could see from the name... |
H: Count the max number of consecutive 1 and 0 in Pandas Dataframe
Hey I have the following Dataset
import pandas as pd
df = pd.DataFrame({
'column1': [0,0,1,0,1,0,0,1,1,0,1,1,1]})
I want to be able to count the number of consecutive 1 and 0 and generate 2 columns as such:
consec0: 1,2,_,1,_,1,2,_,_,1,_,_,_
conse... |
H: How to select 'cutoff' of classifier probability
I have recently used xgboost to conduct binary classification in an nlp problem. The idea was to identify if a particular article belonged to an author or not, pretty standard exercise.
The results are outputted as a probability between 0 and 1, and there is the ocas... |
H: How is the fit function in SimpleImputer working to find the mean in the Salary column as well when just the Age column is given as its argument?
The only argument inside the fit function of SimpleImputer is: 'Age'. Yet the returned output worked on the 'Salary' column as well. That is what I am unable to understan... |
H: What's the complexity of HDBSCAN?
I can't find any complexity information about HDBSCAN by google or wiki.
And how about compare to OPTICS?
AI: By googling: HDBSCAN is order of n squared whereas optics is order of n times log(n). |
H: decision -tree regression to avoid multicollinearity for regression model?
I read in comments a recommendation for decision tree´s instead of linear models like neural network, when the dataset has many correlated features. Because to avoid multicollinearity.
A similar question is already placed, but not really ans... |
H: How do reshape an image to fit my Mnist Convolutional model?
I have done research but cannot seem to find what's wrong here
I have created this model for Mnist digit clasification :
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import ... |
H: Cleaning a certain feature to predict salary using Machine Learning
Info:
I am working on a dataset, and i would like to create a model that would predict salary.
Columns are as follows:
Index(['ID', 'Salary', 'DOJ', 'DOL', 'Designation', 'JobCity', 'Gender', 'DOB',
'10percentage', '10board', '12percentage',... |
H: Keras model.predict giving different shape from training label array
I'm using the following code to try and learn tensorflow. I've clearly specified the shapes of the training and validation X and y arrays.
import numpy as np
import tensorflow as tf
f = lambda x: 2*x
Xtrain = np.random.rand(400,1)
ytrain = f(Xtra... |
H: Layer weights don't match in keras
This question uses the following code:
Xtrain = np.random.rand(400,1)
ytrain = f(Xtrain)
Xval = np.random.rand(200,1)
yval = f(Xval)
model = tf.keras.models.Sequential([
tf.keras.layers.Dense(10, activation='relu'),
#tf.keras.layers.Dense(10, activation='relu'),
tf.ke... |
H: How to find correlation between categorical data and continuous data
I'm working on imputing null values in the Titanic dataset.
The 'Embarked' column has some. I do NOT want to just set them all to the most common value, 'S'.
I want to impute 'Embarked' based on its correlation with the other columns.
I have tried... |
H: Text classification with Word2Vec on a larger corpus
I am working on a small project and I would like to use the word2vec technique as a text representation method. I need to classify patents but I have only a few of them labelled and to increase the performance of my ML model, I would like to increase the corpus/... |
H: Explanation on some steps of AdaBoost.R2
I am trying to understand AdaBoost.R2 in order to implement it and apply it to a regression problem. In this circumstances I need to understand it perfectly, however there's some step i don't really get.
The paper is available here, and Adaboost.R2 is presented in section 3:... |
H: Why can't I specify the correct NumPy size?
In the network (model of Keras, Sequential), the input layer must have 4 neurons. The input must be 1 list, the length of which is 4, each element is a number.
print("SHAPE:", np.array([1, 1, 1, 1]).shape)
self.model.fit(np.array([1, 1, 1, 1]),
self.rightAnswer,
epochs ... |
H: Logistic regression does cannot converge without poor model performance
I have a multi-class classification logistic regression model. Using a very basic sklearn pipeline I am taking in cleansed text descriptions of an object and classifying said object into a category.
logreg = Pipeline([('vect', CountVectorizer()... |
H: Forecasting using Python
I have very less training observations (15). I need to predict 6 months into the future. What forecasting model is best suited for this scenario? Here is how my dataset looks
Month | Response Rate |% Promoters |% Detractors |%Neutrals
2019-01-01 | 5% ... |
H: How do stacked CNN layers work?
The internet is full of pictures like this:
But how are the second/third/etc CNN layers able to extract features when the features are already extracted by the previous layers?
For example, the mid-level feature in the picture has a nose. When we apply this "nose" filter, the output... |
H: Why is batch size limited by RAM?
The parameters of the network are changed to minimize the loss on the mini-batch, but usually the loss on the mini-batch is just the (weighted) sum of losses on each datum individually. Loosely, I would represent this as
$$ dT = \frac{1}{\text{batch_size}} \sum_{i \in \text{batch}}... |
H: How do we get the coefficients and intercept in Logistic Regression?
I'm using Codecademy to learn about logistic regression and there are some holes in my understanding of this topic.
import numpy as np
hours_studied = np.array([[ 0],[ 1],[ 2],[ 3],[ 4],[ 5],[ 6],[ 7],[ 8],[ 9],[10],[11],[12],[13],[14],[15],[16],... |
H: Function extrapolation
I have a list
[1.0, 0.488, 0.300, 0.213, 0.163, 0.127]
Plot (dont have enough reputation to post an image)
I need to extrapolate this function for 15 more points further, asymptote is 0.
I figured out that maybe I need a custom kernel for SVR (something like y=1/x), but I havent found any ex... |
H: What does it mean that an hypotesis is consistent?
I am studying concept learning, and I am focusing on the concept of consistency for an hypotesis.
Consider an Hypotesis $h$, I have understood that it is consistent with a training set $D$ iff $h(x)=c(x)$ where $c(x)$ is the concept and this has to be verified for ... |
H: Tensorflow.Keras: How to get gradient for an output class w.r.t a given input?
I have implemented and trained a sequential model using tf.keras. Say I am given an input array of size 8X8 and an output [0,1,0,...(rest all 0)].
How to calculate the gradient of the input w.r.t to the given output?
model = ...
output =... |
H: Test for feature dependencies in time series modelling
I have time-series data that track event occurrence in 3 locations. Here's a sample:
Count Total
Location A B C
Date
2018-06-22 0 1 1 2
2018-06-23 2 1 0 3
2018-06-24 0 0 1 ... |
H: What does it exactly mean when we say that PCA and LDA are linear methods of learning data representation?
I have been reading on representation learning and I have come across this idea that PCA and LDA are linear methods of data representation, however, auto-encoders provide a non-linear way. Does this mean that ... |
H: Mathematics: Can the result of a derivative for the Gradient Descent consist of only one value?
I have a problem of a task using the formula of the Gradient Descent:
Perform two steps of the gradient descent towards a local minimum for the function given below, using a step size of 0.1 and an initial value of [1, ... |
H: What kind of data (in context of trends in data) is Logistic Regression appropriate for?
I'm not able to visualise what kind of 'trends' I would have to observe in multi-featured data to be able to say 'Logistic Regression would work well here'.
For example if I have only 1 feature and if the data is something like... |
H: How does the validation set get used in the training phase?
I am confused about how the validation set is used during the training phase (neural network like CNN)?
In a platform like Matlab or python(Keras), I split my dataset into train set, validation set and test set.
I knew that validation set is used to tune h... |
H: Is using samples from the same person in both trainset and testset considers being a data leakage?
Suppose a neural network is built for a binary classification problem such as recognize the face as a smiley face or not, by using a dataset of 1000 persons and each person has ten images of his face.
If the dataset r... |
H: What is the most straightforward way to visualize color-coded clusters along with the cluster centers?
I have applied the kMeans Clustering algorithm to a dataframe and have gained cluster labels for each row. I had selected only two features.
There are 4 clusters.
I want to visualize the datapoints in 2D plane wit... |
H: Is there a deep learning method for 3D labels?
As the question says, I want to feed labels into a neural net that are three dimensional. Let's say that I have 3 possible labels and each one of my data points corresponds to a percentage of those labels. e.g, my first datapoint contains 20% of label A, 30% of label B... |
H: Training CNN on a huge data set
I am trying to train an AlexNet image model on the RVL-CDIP Dataset. The dataset consists of 320,000 training images, 40,000 validation images, and 40,000 test images.
Since the dataset is huge I started training on 500 (per class) sample from the training set. The result is below:
... |
H: How to compare two clustering solutions when their labelling differs
I am planning to test the reliability of a clustering approach for some data. My plan is to repeatedly (with replacement) draw a number of random subsample pairs (e.g. 2x 10% of the total data), run the clustering on both individually, and then co... |
H: how to create sklearn pipeline object using predtrained standardscalar object
I am having pretrained Sklearn model and pre-trained Standard scalar object saved as pickle . And now I want to create Sklearn pipeline using both of it.
I need sklearn pipeline to convert it into ONNX format.
I couldnt do it as pipeline ... |
H: Does the test set has to be in [0,1] range?
I have standardized training set using
mean = XTrain.mean()
XTrain-=mean
std = XTrain.std()
XTrain/=std
And then used mean and std to standardize validation and test sets. The training and validation sets have values that are greater than 1 and less than zero is that ok... |
H: Fully-Connected DNN: Compute the numbers of free parameter in a DNN
A fully-connected DNN has layer sizes of 3-3-4-2, where the first layer size represents the input layer. We assume that all layers are affine ones (no ReLU). Give the dimensions of all weight matrices and all bias vectors in the network and compute... |
H: LSTM Sequential Model question re: ValueError: non-broadcastable output operand with shape doesn't match broadcast shape
This is probably a very simplistic question but I have not been able to find resources that directly address this. I know I must be understanding this incorrectly; I'm not quite sure how.
I've no... |
H: Is providing class weight to neural network enough for imbalanced binary classification?
I have a highly imbalanced binary classification problem, probably 95:5 for two classes. I don't want to perform resampling as the data is already huge and training it would just take more time. (I'm also aware of down sampling... |
H: Should you use random state or random seed in machine learning models?
I'm starting to study machine learning. All the examples I saw, the person that created the ML model used a random state or a random seed to stop the randomness of the process. But, in real life, when you're trying to apply a machine learning mo... |
H: Fitting multiple line
Short version:
How can I find a function that maps X to Y when data looks like this.
Note:
For a pair of emissivity and distance relation between temperature and
raw_thermal_data is linear.
Long Version:
I am working on a project which uses thermal(IR) camera. Now we extract temperature fro... |
H: Pandas copy() different columns from different dataframes to a new dataframe
I have 2 dataframes that are coming from 2 different Excel files. I want to extract some columns from one file and other columns from the second file to print a new dataframe with the copied columns.
I copied 2 columns from different dataf... |
H: Mathematics: Writing down a three-class classifier confusion matrix
Confusion matrix 2A three-class classifier is evaluated on a test set
of 900 samples which containsall three classes in equal
proportions.
• Classes 2 and 3 are always classified correctly
• Class 1 is confused with class 2 in 50% of the cases,
... |
H: Handling features with multiple values per instance in Python for Machine Learning model
I have a dataset which contains medical data about children and I am developing a predictive machine learning model to predict adverse pregnancy outcomes. The dataset contains mostly features with a single value per child, e.g.... |
H: Does label encoding an entire dataset cause data leakage?
I have a dataset on which one of the features has a lot of different categorical values. Trying to use a LabelEncoder, OrdinalEncoder or a OneHotEncoder results in an error, since when splitting the data, the test set ends up having some values that are not ... |
H: Which is the best method for Neural Network Layers in Keras
In keras we can create neural network layers in many ways.
1. Sequential API.
for example
model=sequential()
2. Functional
for example
x1=Input(shape=(2,)
x2=Dense(2)(x1)
3. Subclassing
for example
class Mymodel(keras.layers.Layers):
def __init__(sel... |
H: Any useful tips on transfer learning for a text classification task
I am doing a supervised binary text classification task.
I want to classify the texts from site A, site B, and site C.
The in-domain performance looks OK for texts of each site. (92%-94% accuracy).
However, if I applied the model trained on texts o... |
H: how come accuracy_score recognizes the positive label and precision_score does not?
I am executing this code which works perfectly for me:
(I only have 'positive' and 'negative' sentiments):
from sklearn import metrics
print('Accuracy:',metrics.accuracy_score(test_sentiments, predicted_sentiments))
print('Precisi... |
H: Back propagation through a simple convolutional neural network
Hi I am working on a simple convolution neural network (image attached below). The input image is 5x5, the kernel is 2x2 and it undergoes a ReLU activation function. After ReLU it gets max pooled by a 2x2 pool, these then are flattened and headed off in... |
H: Can features negatively correlated with the target be used?
In feature selection (for a regression problem), can features that are negatively correlated with the target variable be chosen to predict the target?
I don't think negative correlation means the predictor does not provide any information about the target... |
H: Random Forest with 2D features
I try to predict the position of a specific point (crest) in a 1D signal (elevation profile). Until now, I computed gradient at every point of my signal and combined that with additional features or heuristics to find approximate position of the expected output (position of the crest)... |
H: Logistic regression vs Random Forest on imbalanced data set
I have an imbalanced data set where positives are just 10% of the whole sample. I am using logistic regression and random forest for classification. While comparing the results of these models, I have found that the probability output of logistic regressio... |
H: How to handle sparsely coded features in a dataframe
I have a dataset that contains information regarding diabetes patients, like so:
id diabetes diet insulin lifestyle
0 No NaN NaN NaN
1 Yes Yes Yes NaN
2 No NaN NaN NaN
3 Yes... |
H: Is it possible to have stratified train-test split of a set based on two columns?
Consider a dataframe that contains two columns, text and label. I can very easily create a stratified train-test split using sklearn.model_selection.train_test_split. The only thing I have to do is to set the column I want to use for ... |
H: Measure correlation for categorical vs continous variable
Given a variable which is categorical that depends on continuous variables, I would like to know how to check wether these continous variable explain the categorical one.
So:
Y = cagetorical
X1 = continous
X2 = continous
X3 = continous
I'd start with a co... |
H: Binary classification using images and an external dataset
I currently have a project in which I must create a binary classifier to detect defective products. I have image data which has already been labeled (each part has been labeled as a pass or fail), as well as an external dataset which has specific measuremen... |
H: When does Adam update its weights?
I have a dataset with at least 70% of labels incorrect.
I'd expect that incorrect labels would compensate each other while true labels will be taught properly (given a very large dataset).
For example, if I have 300 samples saying a => -1 and 300 samples saying a => 1, the result ... |
H: What is the right way to store datasets for a CNN project
Our image classification project has thousands of raw photos, masks and reshaped images. We store source code in git. But datasets don't belong to source code version control. How should we store thee sets of images?
AI: You can use google drive to save thes... |
H: Similarity Measure between two feature vectors
I have face identification system with following details:
VGG16 model for feature extraction
512 dimensional feature vector (normalized)
I need to calculate similarity measure between two feature vectors. So far I have tried as difference measure:
Pairwise cosine, e... |
H: Pandas/Python - comparing two columns for matches not in the same row
I have this data:
I wanted to compare A and B for matches not by row but rather search A0 if it is in column B and so on. Moreover, I wanted to ignore the .AX in column A because it would not find any matches in column B anyway.
I used this, but... |
H: what is the difference in terms namely Correlation, correlated and collinearity?
A website says Correlation refers to an increase/decrease in a dependent variable with an increase/decrease in an independent variable. Collinearity refers to two or more independent variables acting in concert to explain the variation... |
H: How to grid search feature selection and neural network hyperparameters in the same grid?
I'm using the GridSearchCV () class from scikit to perform hyperparameter optimization in a sequential neural network. I've built a pipeline to also find the best number of features by putting a feature selector inside the pip... |
H: How can i tell if my model is overfitting from the distribution of predicted probabilities?
all,
i am training light gradient boosting and have used all of the necessary parameters to help in over fitting.i plot the predicted probabilities (i..e probabililty has cancer) distribution from the model (after calibratin... |
H: Is always converting a input vector into matrix and apply cnn's good idea?
I know the benefits of using cnns(reduced size weight matrices). Is it a good idea to convert a input vector(which is not a image) into a matrix and apply cnn's. What I understand is that it should not be done because this would enforce some... |
H: Machine learning detect changes in components
I am a student who will finish my studies next year and I want to analyze the job market in advance. I have found an interesting job where it says:
The department of assemblies and systems of the X deals with the simulation, testing and evaluation of components, assemb... |
H: How is this score function estimator derived?
In this paper they have this equation, where they use the score function estimator, to estimate the gradient of an expectation. How did they derive this?
AI: This is simply a special case (where $p_\psi = N(0,1)$) of the general gradient estimator for Natural Evolution ... |
H: what make lightGBM run faster than XGBoost?
I am curious on what differences in implementation allow speed up of lightGBM over XGBoost, some times up to magnitude of orders.
AI: First of all both the GBM methods are great and superiority of each algorithm is dependent on the data.
Major Differences between the two ... |
H: How do we know a neural network test accuracy is good enough when results vary with different runs?
In every paper I read about prediction models, the training accuracy and the test accuracy (sometimes also the validation accuracy) is stated as a discrete number. However, in experience, depending on how the weights... |
H: pytorch convolution with 0-stride along one dimension
For some square images, I'd like to use torch.nn.Conv2d with the kernel as a vertical block. As in, the kernel size is defined as max value of the first dimension by 1. Since the first dimension has no more room, I'd like to have 0 stride along that first dimens... |
H: "Change the features of a CNN into a grid to fed into RNN Encoder?" What is meant by that?
So in the paper for OCR pr LaTex formula extraction from image What You Get Is What You See: A Visual Markup Decompiler, they pass the features of the CNN into RNN Encoder. But there is problem that rather than passing the fe... |
H: What criteria use in order to select the best internal validation for clustering?
I am doing homework about how to evaluate a clustering algorithm both hierarchical and partitional.
For doing this I have a dataset that I can plot as you can see:
The clustering algorithms that I am using are K-Means, Gaussian mixtu... |
H: Why naive bayes is "naive"
Some articles say that naive Bayes is naive because of "independence of attributes". Whereas others say "independence of attributes within a class". Can anybody please clear this confusion?
Thanks
AI: Naive Bayes doesn't assume independence of attributes ... It assumes conditional indepen... |
H: Logic behind the Statement on Non-Parametric models
I am currently reading 'Mastering Machine Learning with scikit-learn', 2E, by Packt. In Lazy Learning and Non-Parametric models topic in Chapter 3- Classification and Regression with k-Nearest Neighbors, there is a paragraph stating-
Non-parametric models can be u... |
H: Python writing to Excel file: writerow() takes no keyword arguments
I have this script:
import requests
from requests import get
from bs4 import BeautifulSoup
import csv
import pandas as pd
f = open('olanda.csv', 'wb')
writer = csv.writer(f)
url = ('https://www......')
response... |
H: Why Adaboost SAMME needs f to be estimable?
I am trying to understand the mathematics behind SAMME AdaBoost:
At some stage, the paper adds a constraint for f to be estimable:
I do not understand why this is required. Can someone explain a bit better why this restriction is needed?
As well, would be possible to use... |
H: Using word embeddings with additional features
I have the set of queries for classification task using Gradient Boosting Classifier of scikit learn. I want to enrich the model by feeding additional features along with GloVe. How should I approach scaling in this case? GloVe is already well scaled, however, features... |
H: Learn (common) grammar / pattern from set of sample strings?
So I currently have a text pattern detection challenge to solve at work. I am trying to make an outlier detection algorithm for a database, for string columns.
For example let's say I have the following list of strings:
["abc123", "jkj577", "lkj123", "uio... |
H: What is Happening in the training process when we are fitting a model to the data
In any prediction task, the process of “fitting” a model to the data observed in the training process can be best described as...
Assessing all observations available and then backsolving for the dimensionality of best fit.
Making us... |
H: Wrong result when solving: "chance that two random cards differ in color and value?"
I'm trying to build a simulation for this question:
"There are 50 cards of 5 different colors. Each color has cards
numbered between 1 to 10. You pick 2 cards at random. What is the
probability that they are not of same color and ... |
H: Multiple output size in neural network
In the paper "A NOVEL FOCAL TVERSKY LOSS FUNCTION WITH IMPROVED ATTENTIONU-NETFOR LESION SEGMENTATION" the author use deep supervision by outputing multiple outputmask which have different scale.
I do not understand how it can work with regards to the loss function. y_pred and... |
H: Which deep learning network would be suitable for classifying this kind of text data?
I have some experience with images and have played around with image classification using CNN's but have limited knowledge when it comes to text data.
The input that I currently want to classify is written as:
hjkhghkgfghjkhghkgfg... |
H: Why Davies-Bould chose a number ob cluster higher than Silhouette or Calinsky Harabasz?
I am doing use several metrics in order to know what number of clusters is correct in order to do this I selected 3 clustering algorithms and 3 internal evaluation metrics, Silhouette, Calinsky Harbasz and Davies Bouldin.
The re... |
H: How to cluster government census data in order to group Metropolitan statistical areas
I have collected a bunch of census data from 2012 - 2018. I wanted to apply some clustering algorithms in order to compare Metropolitan statistical area (MSA's). Ideally once I run the clustering algorithm I would like to see whi... |
H: How to Make Meaningful Conclusions here?
I recently appeared for an Interview for my college and I was asked the following question. The Interviewer said that this question was a Data Science question.
The question-
Suppose 7.5% of the population has a certain Bone Disease. During COVID pandemic you go to a hospita... |
H: How to encode ordinal data before applying linear regression in STATA?
I have a data set that has student performance marks (continuous and dependent variable), Teacher Qualification (Ordinal and independent variable containing categories: Masters, Bachelors, High School). I want to apply the regression analysis to... |
H: Anybody know what this type of visualisation is called?
I think this is a pretty cool way to visualise changes in values but I can’t find any name for this type of visualisation.
I
Source: https://www.economist.com/graphic-detail/2020/07/28/americans-are-getting-more-nervous-about-what-they-say-in-public
AI: This t... |
H: Consolidating multivariate time-series information from many data sets
I am having trouble setting up a problem with regards to time series analysis. I have 30 data sets, where each set corresponds to a certain project. Each project has 7 features, and each feature has time series information sampled every week fro... |
H: How do we decide between XGBoost, RandomForest and Decision tree?
What do we take into consideration while deciding which technique should be used when dealing with a particular dataset? I understand that there isn't any hard and fast rule to this. Do we use XGBoost only when there are a lot of features in the data... |
H: How is the backbone of two neural networks trained?
Suppose, I have a backbone network(convolutional neural network). After this network ends, the output is fed into two neural networks. Both building on the outputs of the feature extractor(CNN). Now if I want to train this complete network from scratch on two diff... |
H: For NLP, is GPT-3 better than RoBERTa?
I am learning deep learning and I want to get into NLP. I have done LSTM, and now I am learning about vectorisation and transformers. Can you please tell me, which algorithm is more effective and accurate?
AI: They are meant for different purposes and they are hardly comparabl... |
H: How do I know what the best number of layers is required to achieve the highest accuracy
I'm learning from Udacity using this video.
I saw this piece of code:
model = nn.Sequential(nn.Linear(784, 128),
nn.ReLU(),
nn.Linear(128, 64),
nn.ReLU(),
... |
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