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Haitao Du
  • Member for 6 years, 2 months
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58 votes

Regularization methods for logistic regression

54 votes

Why is 600 out of 1000 more convincing than 6 out of 10?

43 votes
Accepted

Is there any intuitive explanation of why logistic regression will not work for perfect separation case? And why adding regularization will fix it?

38 votes
Accepted

How could stochastic gradient descent save time compared to standard gradient descent?

33 votes

Is an overfitted model necessarily useless?

28 votes

Are neural networks better than SVMs?

28 votes
Accepted

Boosting: why is the learning rate called a regularization parameter?

26 votes
Accepted

Do all machine learning algorithms separate data linearly?

26 votes
Accepted

Is low bias in a sample a synonym for high variance?

24 votes

Binary classification with strongly unbalanced classes

23 votes
Accepted

How does linear base learner works in boosting? And how does it works in the xgboost library?

23 votes

Cohen's kappa in plain English

22 votes

Why use gradient descent for linear regression, when a closed-form math solution is available?

22 votes
Accepted

How to decide between PCA and logistic regression?

22 votes
Accepted

Why does feature engineering work ?

19 votes
Accepted

what makes neural networks a nonlinear classification model?

19 votes

What makes a classifier misclassify data?

15 votes

How do R and Python complement each other in data science?

14 votes
Accepted

How to know if a learning curve from SVM model suffers from bias or variance?

13 votes

What are the four axes on PCA biplot?

13 votes

To maximize the chance of correctly guessing the result of a coin flip, should I always choose the most probable outcome?

12 votes

If I want an interpretable model, are there methods other than Linear Regression?

12 votes

How do I know my k-means clustering algorithm is suffering from the curse of dimensionality?

12 votes

How to run linear regression in a parallel/distributed way for big data setting?

12 votes

Why study convex optimization for theoretical machine learning?

12 votes
Accepted

Error increase on L2 regularization in an NN

11 votes

What I should do if no distribution fits my dataset?

11 votes
Accepted

Can duplicate examples create multi-collinearity?

11 votes

What does it mean for a linear regression to be statistically significant but has very low r squared?

11 votes
Accepted

Avoid overfitting in regression: alternatives to regularization

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