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Top Questions
114
votes
Is it possible to train a neural network without backpropagation?
machine-learning
neural-networks
optimization
backpropagation
asked Sep 20, 2016 at 1:48
stats.stackexchange.com
43
votes
Is LSTM (Long Short-Term Memory) dead?
machine-learning
natural-language
lstm
sequence-analysis
asked Jun 18, 2020 at 9:44
stats.stackexchange.com
39
votes
Why are survival times assumed to be exponentially distributed?
distributions
survival
assumptions
exponential
asked Mar 17, 2017 at 15:10
stats.stackexchange.com
34
votes
What exactly is the difference between a parametric and non-parametric model?
machine-learning
neural-networks
nonparametric
terminology
parametric
asked Mar 20, 2017 at 13:54
stats.stackexchange.com
33
votes
Why are symmetric positive definite (SPD) matrices so important?
mathematical-statistics
optimization
covariance-matrix
intuition
linear-algebra
asked Jul 15, 2016 at 19:13
stats.stackexchange.com
33
votes
If I generate a random symmetric matrix, what's the chance it is positive definite?
probability
matrix
random-generation
eigenvalues
random-matrix
asked Jan 8, 2018 at 18:54
stats.stackexchange.com
32
votes
Can degrees of freedom be a non-integer number?
r
degrees-of-freedom
gam
asked May 21, 2017 at 17:00
stats.stackexchange.com
30
votes
What are the impacts of choosing different loss functions in classification to approximate 0-1 loss
machine-learning
classification
optimization
loss-functions
asked Jul 7, 2016 at 12:58
stats.stackexchange.com
29
votes
When should we discretize/bin continuous independent variables/features and when should not?
machine-learning
continuous-data
feature-construction
binning
asked Aug 19, 2016 at 17:31
stats.stackexchange.com
28
votes
Why there are two different logistic loss formulation / notations?
logistic
generalized-linear-model
notation
loss-functions
asked Aug 13, 2016 at 9:10
stats.stackexchange.com
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Top Answers
58
Regularization methods for logistic regression
stats.stackexchange.com
55
Why is 600 out of 1000 more convincing than 6 out of 10?
stats.stackexchange.com
43
Is there any intuitive explanation of why logistic regression will not work for perfect separation case? And why adding regularization will fix it?
stats.stackexchange.com
38
How could stochastic gradient descent save time compared to standard gradient descent?
stats.stackexchange.com
33
Is an overfitted model necessarily useless?
stats.stackexchange.com
28
Boosting: why is the learning rate called a regularization parameter?
stats.stackexchange.com
28
Are neural networks better than SVMs?
stats.stackexchange.com
26
Do all machine learning algorithms separate data linearly?
stats.stackexchange.com
26
Is low bias in a sample a synonym for high variance?
stats.stackexchange.com
24
Binary classification with strongly unbalanced classes
stats.stackexchange.com
23
How does linear base learner works in boosting? And how does it works in the xgboost library?
stats.stackexchange.com
23
Cohen's kappa in plain English
stats.stackexchange.com
22
Why does feature engineering work ?
stats.stackexchange.com
22
Why use gradient descent for linear regression, when a closed-form math solution is available?
stats.stackexchange.com
22
How to decide between PCA and logistic regression?
stats.stackexchange.com
19
what makes neural networks a nonlinear classification model?
stats.stackexchange.com
19
What makes a classifier misclassify data?
stats.stackexchange.com
16
How do R and Python complement each other in data science?
stats.stackexchange.com
14
How to know if a learning curve from SVM model suffers from bias or variance?
stats.stackexchange.com
13
To maximize the chance of correctly guessing the result of a coin flip, should I always choose the most probable outcome?
stats.stackexchange.com
13
What are the four axes on PCA biplot?
stats.stackexchange.com
12
If I want an interpretable model, are there methods other than Linear Regression?
stats.stackexchange.com
12
Error increase on L2 regularization in an NN
stats.stackexchange.com
12
Why study convex optimization for theoretical machine learning?
stats.stackexchange.com
12
How do I know my k-means clustering algorithm is suffering from the curse of dimensionality?
stats.stackexchange.com
12
How to run linear regression in a parallel/distributed way for big data setting?
stats.stackexchange.com
11
Can duplicate examples create multi-collinearity?
stats.stackexchange.com
11
What I should do if no distribution fits my dataset?
stats.stackexchange.com
11
Avoid overfitting in regression: alternatives to regularization
stats.stackexchange.com
11
What does it mean for a linear regression to be statistically significant but has very low r squared?
stats.stackexchange.com
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