User mlai

1259 votes

27 answers

839k views

Making sense of principal component analysis, eigenvectors & eigenvalues

claws

12.9k

asked Sep 15, 2010 at 20:05

530 votes

23 answers

286k views

Why square the difference instead of taking the absolute value in standard deviation?

standard-deviation definition absolute-value faq

c4il

5,545

asked Jul 19, 2010 at 21:04

416 votes

14 answers

269k views

Bayesian and frequentist reasoning in plain English

bayesian frequentist

Daniel Vassallo

4,269

asked Jul 19, 2010 at 19:25

269 votes

10 answers

154k views

How would you explain covariance to someone who understands only the mean?

variance covariance intuition teaching

PhD

13.7k

asked Nov 7, 2011 at 19:41

204 votes

4 answers

193k views

What does the hidden layer in a neural network compute?

machine-learning neural-networks nonlinear-regression

FAtBalloon

2,177

asked Jul 2, 2013 at 15:59

149 votes

3 answers

220k views

Help me understand Bayesian prior and posterior distributions

distributions bayesian prior posterior

Bob

1,491

asked May 9, 2013 at 13:51

138 votes

3 answers

272k views

What is the difference between linear regression and logistic regression?

regression logistic linear-model

B Seven

2,903

asked May 28, 2012 at 18:17

130 votes

5 answers

75k views

How does a Support Vector Machine (SVM) work?

machine-learning classification svm statistical-learning

tdc

7,389

asked Feb 16, 2012 at 13:25

99 votes

30 answers

53k views

Is there a way to remember the definitions of Type I and Type II Errors?

terminology type-i-and-ii-errors

Thomas Owens

1,091

asked Aug 12, 2010 at 19:55

83 votes

14 answers

18k views

When (if ever) is a frequentist approach substantively better than a Bayesian?

bayesian frequentist philosophical

jsakaluk

5,166

asked Feb 4, 2016 at 16:27

82 votes

1 answer

8k views

Help me understand Support Vector Machines

machine-learning classification svm

rohanbk

1,187

asked Oct 24, 2010 at 15:11

80 votes

2 answers

24k views

What is a "kernel" in plain English?

kernel-trick kernel-smoothing

Neil McGuigan

9,452

asked Sep 9, 2010 at 0:15

77 votes

6 answers

134k views

What are i.i.d. random variables?

random-variable intuition iid

user333

6,761

asked Feb 7, 2011 at 13:59

60 votes

13 answers

50k views

Does 10 heads in a row increase the chance of the next toss being a tail?

probability independence intuition games bernoulli-process

user68492

601

asked Feb 9, 2015 at 8:15

54 votes

3 answers

14k views

Understanding Naive Bayes

machine-learning naive-bayes

G Gr

1,001

asked Jan 27, 2012 at 17:29

50 votes

5 answers

41k views

How does rectilinear activation function solve the vanishing gradient problem in neural networks?

machine-learning neural-networks deep-learning gradient-descent

Hans-Peter Störr

617

asked Oct 13, 2015 at 20:05

38 votes

5 answers

9k views

How to visualize/understand what a neural network is doing?

data-visualization neural-networks

rm999

758

asked Jun 9, 2011 at 17:19

37 votes

8 answers

15k views

What is Bayes' theorem all about?

probability bayesian mathematical-statistics

user333

6,761

asked Jul 26, 2010 at 20:30

33 votes

3 answers

13k views

In boosting, why are the learners "weak"?

machine-learning mathematical-statistics boosting

tdc

7,389

asked Feb 16, 2012 at 13:37

28 votes

2 answers

7k views

Support vector machines and regression

regression machine-learning svm

Zach

22.4k

asked Jul 18, 2011 at 14:29

27 votes

3 answers

14k views

Why break down the denominator in Bayes' Theorem?

bayesian

Ram Rachum

671

asked Oct 11, 2010 at 23:45

25 votes

11 answers

23k views

Why is logistic regression called a machine learning algorithm?

machine-learning logistic random-forest

Metariat

2,376

asked Jun 25, 2015 at 12:57

24 votes

2 answers

8k views

Structural Equation Models (SEMs) versus Bayesian Networks (BNs)

structural-equation-modeling bayesian-network causality

zkurtz

2,070

asked Jun 12, 2014 at 19:22

23 votes

2 answers

3k views

On the "strength" of weak learners

machine-learning boosting ensemble-learning

Amelio Vazquez-Reina

18k

asked Jul 28, 2011 at 19:42

23 votes

2 answers

9k views

How does boosting work?

machine-learning boosting

Łukasz Lew

1,332

asked Jul 20, 2010 at 9:34

22 votes

3 answers

22k views

Normalizing constant in Bayes theorem

probability bayesian

amateur

374

asked Jun 20, 2011 at 3:38

20 votes

2 answers

5k views

How to apply Bayes' theorem to the search for a fisherman lost at sea

probability bayesian posterior search-theory

mlai

493

asked Oct 14, 2014 at 2:47

18 votes

2 answers

5k views

Deep learning vs. Decision trees and boosting methods

machine-learning deep-learning cart restricted-boltzmann-machine adaboost

Amelio Vazquez-Reina

18k

asked Jul 5, 2011 at 21:11

15 votes

1 answer

5k views

How does gentle boosting differ from AdaBoost?

machine-learning boosting

Vebjorn Ljosa

523

asked Jul 20, 2010 at 16:01

13 votes

5 answers

6k views

Appropriate clustering techniques for temporal data?

machine-learning clustering

histelheim

2,483

asked Aug 26, 2012 at 20:17

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Making sense of principal component analysis, eigenvectors & eigenvalues

Why square the difference instead of taking the absolute value in standard deviation?

Bayesian and frequentist reasoning in plain English

How would you explain covariance to someone who understands only the mean?

What does the hidden layer in a neural network compute?

Help me understand Bayesian prior and posterior distributions

What is the difference between linear regression and logistic regression?

How does a Support Vector Machine (SVM) work?

Is there a way to remember the definitions of Type I and Type II Errors?

When (if ever) is a frequentist approach substantively better than a Bayesian?

Help me understand Support Vector Machines

What is a "kernel" in plain English?

What are i.i.d. random variables?

Does 10 heads in a row increase the chance of the next toss being a tail?

Understanding Naive Bayes

How does rectilinear activation function solve the vanishing gradient problem in neural networks?

How to visualize/understand what a neural network is doing?

What is Bayes' theorem all about?

In boosting, why are the learners "weak"?

Support vector machines and regression

Why break down the denominator in Bayes' Theorem?

Why is logistic regression called a machine learning algorithm?

Structural Equation Models (SEMs) versus Bayesian Networks (BNs)

On the "strength" of weak learners

How does boosting work?

Normalizing constant in Bayes theorem

How to apply Bayes' theorem to the search for a fisherman lost at sea

Deep learning vs. Decision trees and boosting methods

How does gentle boosting differ from AdaBoost?

Appropriate clustering techniques for temporal data?