Methods and principles of building "computer systems that automatically improve with experience."

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150
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15answers
28k views

The Two Cultures: statistics vs. machine learning?

Last year, I read a blog post from Brendan O'Connor entitled "Statistics vs. Machine Learning, fight!" that discussed some of the differences between the two fields. Andrew Gelman responded favorably ...
32
votes
12answers
4k views

Machine learning cookbook / reference card / cheatsheet?

I find resources like the Probability and Statistics Cookbook and The R Reference Card for Data Mining incredibly useful. They obviously serve well as references but also help me to organize my ...
28
votes
8answers
4k views

Feature selection for “final” model when performing cross-validation in machine learning

I am getting a bit confused about feature selection and machine learning and I was wondering if you could help me out. I have a microarray dataset that is classified into two groups and has 1000s of ...
67
votes
11answers
36k views

What is the difference between data mining, statistics, machine learning and AI?

What is the difference between data mining, statistics, machine learning and AI? Would it be accurate to say that they are 4 fields attempting to solve very similar problems but with different ...
46
votes
1answer
2k views

Help me understand Support Vector Machines

I understand the basics of what a Support Vector Machines' aim is in terms of classifying an input set into several different classes, but what I don't understand is some of the nitty-gritty details. ...
32
votes
5answers
4k views

Training with the full dataset after cross-validation?

Is it always a good idea to train with the full dataset after k-fold cross-validation? Or is it better instead to stick with one of the models learned in one of the cross-validation splits for ...
62
votes
5answers
6k views

What skills are required to perform large scale statistical analyses?

Many statistical jobs ask for experience with large scale data. What are the sorts of statistical and computational skills that would be need for working with large data sets. For example, how about ...
32
votes
5answers
24k views

What is the difference between test set and validation set?

I found this confusing when I use the neural network toolbox in Matlab. It divided the raw data set into three parts: training set validation set test set I notice in many training or learning ...
19
votes
2answers
3k views

Proper way of using recurrent neural network for time series analysis

Recurrent neural networks differ from "regular" ones by the fact that they have a "memory" layer. Due to this layer, recurrent NN's are supposed to be useful in time series modelling. However, I'm not ...
10
votes
0answers
1k views

Machine learning self-learning book? [duplicate]

Possible Duplicate: Machine learning cookbook / reference card / cheatsheet? I wonder if there is a good self-learning textbook for machine learning? I am particularly looking for those in ...
21
votes
6answers
4k views

Can you recommend a book to read before Elements of Statistical Learning?

Based on this post, http://quant.stackexchange.com/questions/111/how-can-i-go-about-applying-machine-learning-algorithms-to-stock-markets, I want to digest Elements of Statistical Learning. ...
8
votes
3answers
2k views

Comparing clusterings: Rand Index vs Variation of Information

I was wondering if anybody had any insight or intuition behind the difference between the Variation of Information and the Rand Index for comparing clusterings. I have read the paper "Comparing ...
8
votes
2answers
1k views

How does linear discriminant analysis reduce the dimensions?

There are words from "The Elements of Statistical Learning" on page 91: The K centroids in p-dimensional input space span at most K-1 dimensional subspace, and if p is much larger than K, this ...
19
votes
3answers
1k views

Understanding Naive Bayes

To demonstrate the concept of Naïve Bayes Classification, consider the example displayed in the illustration above. As indicated, the objects can be classified as either GREEN or RED. My task is to ...
12
votes
4answers
5k views

How and why do normalization and feature scaling work?

I see that lots of machine learning algorithms work better with mean cancellation and covariance equalization. For example, Neural Networks tend to converge faster, and K-Means generally gives better ...
12
votes
2answers
1k views

How to get started with neural networks

I'm completely new to neural networks but highly interested in understanding them. However it's not easy at all to get started. Could anyone recommend a good book or any other kind of resource? Is ...
27
votes
8answers
916 views

How can I help ensure testing data does not leak into training data?

Suppose we have someone building a predictive model, but that someone is not necessarily well-versed in proper statistical or machine learning principles. Maybe we are helping that person as they are ...
15
votes
3answers
10k views

Things to consider about masters programs in statistics

It is admission season for graduate schools. I (and many students like me) am now trying to decide which statistics program to pick. What are some things those of you who work with statistics ...
14
votes
2answers
2k views

Cross Validation (error generalization) after model selection

Note: Case is n>>p I am reading Elements of Statistical Learning and there are various mentions about the "right" way to do cross validation( e.g. page 60, page 245). Specifically, my question is how ...
8
votes
1answer
851 views

Least angle regression keeps the correlations monotonically decreasing and tied?

I'm trying to solve a problem for least angle regression (LAR). This is a problem 3.23 on page 97 of Hastie et al., Elements of Statistical Learning, 2nd. ed. (5th printing). Consider a regression ...
12
votes
2answers
731 views

Supervised learning with “rare” events, when rarity is due to the large number of counter-factual events

Suppose you get to observe "matches" between buyers and sellers in a market. You also get to observe characteristics of both buyers and sellers which you would like to use to predict future matches ...
15
votes
2answers
2k views

Variance estimates in k-fold cross-validation

K-fold cross-validation can be used to estimate the generalization capability of a given classifier. Can I (or should I) also compute a pooled variance from all validation runs in order to obtain a ...
10
votes
2answers
939 views

What happens when you apply SVD to a collaborative filtering problem? What is the difference between the two?

In Collaborative filtering, we have values that are not filled in. Suppose a user did not watch a movie then we have to put an 'na' in there. If I am going to take an SVD of this matrix, then I have ...
8
votes
1answer
3k views

Clustering: Should I use the Jensen-Shannon Divergence or its square?

I am clustering probability distributions using the Affinity Propagation algorithm, and I plan to use Jensen-Shannon Divergence as my distance metric. Is it correct to use JSD itself as the distance, ...
5
votes
1answer
286 views

What do “real values” refer to in supervised classification?

I'm using supervised classification algorithms from mlpy to classify things into two groups for a question-answering system. I don't really know how these algorithms work, but they seem to be doing ...
4
votes
3answers
3k views

Comparing two classifier accuracy results for statistical significance with t-test

I want to compare the accuracy of two classifiers for statistical significance. Both classifiers are run on the same data set. This leads me to believe I should be using a one sample t-test from what ...
3
votes
2answers
570 views

Trouble applying hidden Markov models

Edit: I updated the question to hopefully make it more easy to understand. I think it was overly complex. I’m having a problem applying hidden Markov models to a game I’m building to learn about ...
45
votes
9answers
17k views

Having a job in data-mining without a PhD

I've been very interested in data-mining and machine-learning for a while, partly because I majored in that area at school, but also because I am truly much more excited trying to solve problems that ...
16
votes
12answers
16k views

Best books for an introduction to statistical data analysis?

I bought this book: How to Measure Anything: Finding the Value of Intangibles in Business and Head First Data Analysis: A Learner's Guide to Big Numbers, Statistics, and Good Decisions What ...
27
votes
3answers
8k views

How to compute precision/recall for multiclass-multilabel classification?

I'm wondering how to calculate precision and recall measures for multiclass multilabel classification, i.e. classification where there are more than two labels, and where each instance can have ...
16
votes
6answers
2k views

Alternatives to classification trees, with better predictive (e.g: CV) performance?

I am looking for an alternative to Classification Trees which might yield better predictive power. The data I am dealing with has factors for both the explanatory and the explained variables. I ...
24
votes
2answers
5k views

Choice of K in K-Fold cross validation

I've been using the K-Fold cross validation a few times now to evaluate performance of some learning algorithms, but I've always been puzzled as to how I should choose the value of K. I've often seen ...
21
votes
6answers
2k views

Data mining: How should I go about finding the functional form?

I'm curious about repeatable procedures that can be used to discover the functional form of the function y = f(A, B, C) + error_term where my only input is a set of ...
18
votes
2answers
1k views

Sites for predictive modeling competitions

I participate in predictive modeling competitions on Kaggle, TunedIt, and CrowdAnalytix. I find that these sites are a good way to "work-out" for statistics/machine learning. Are there any other ...
16
votes
2answers
3k views

Restricted Boltzmann machines vs multilayer neural networks

I've been wanting to experiment with a neural network for a classification problem that I'm facing. I ran into papers that talk of RBMs. But from what I can understand, they are no different from ...
16
votes
6answers
2k views

Variable selection procedure for binary classification

What are the variable/feature selection that you prefer for binary classification when there are many more variables/feature than observations in the learning set? The aim here is to discuss what is ...
14
votes
2answers
919 views

When is “Nearest Neighbor” meaningful, today?

In 1999, Beyer et al. asked, When is "Nearest Neighbor" meaningful? Are there better ways of analyzing and visualizing the effect of distance flatness on NN search since 1999? Does [a given] data ...
11
votes
5answers
3k views

Programmer looking to break into machine learning field

I am a software developer (mostly .NET and Python about 5 years experience). What can I do to help me get a job in the machine learning field or really anything that will get me started in that field? ...
9
votes
2answers
4k views

Computing the decision boundary of a linear SVM model

Given the support vectors of a linear SVM, how can I compute the equation of the decision boundary?
8
votes
3answers
1k views

Cross-validation or bootstrapping to evaluate classification performance?

What is the most appropriate sampling method to evaluate the performance of a classifier on a particular data set and compare it with other classifiers? Cross-validation seems to be standard practice, ...
14
votes
5answers
3k views

Can SVM do stream learning one example at a time?

I have a streaming data set, examples are available one at a time. I would need to do multi class classification on them. As soon as I fed a training example to the learning process, I have to discard ...
9
votes
6answers
2k views

What math subjects would you suggest to prepare for data mining and machine learning?

I'm trying to put together a self-directed math curriculum to prepare for learning data mining and machine learning. This is motivated by starting Andrew Ng's machine learning class on Coursera and ...
15
votes
4answers
3k views

Is a strong background in maths a total requisite for ML?

I'm starting to want to advance my own skillset and I've always been fascinated by machine learning. However, six years ago instead of pursuing this I decided to take a completely unrelated degree to ...
10
votes
1answer
1k views

Optimising for Precision-Recall curves under class imbalance

I have a classification task where I have a number of predictors (one of which is the most informative), and I am using the MARS model to construct my classifier (I am interested in any simple model, ...
6
votes
2answers
2k views

How to statistically compare the performance of machine learning classifiers?

Based on estimated classification accuracy, I want to test whether one classifier is statistically better on a base set than another classifier . For each classifier, I select a training and testing ...
8
votes
0answers
282 views

Updating classification probability in logistic regression through time

I am building a predictive model that forecasts a student's probability of success at the end of a term. I’m specifically interested in whether the student succeeds or fails, where success is usually ...
6
votes
2answers
905 views

Building background for machine learning for CS student

I am a CS graduate student and I am starting to get really interested in Machine Learning (and Predictive Analytics). I have started working on a text classification project with a professor to learn ...
2
votes
1answer
179 views

When is a proper scoring rule a better estimate of generalization in a classification setting?

A typical approach to solving a classification problem is to identify a class of candidate models, and then perform model selection using some procedure like cross validation. Typically one selects ...
5
votes
2answers
206 views

Dependent Bernoulli trials

The probability of a sequence of n independent Bernoulli trials can be easily expressed as $$p(x_1,...,x_n|p_1,...,p_n)=\prod_{i=1}^np_i^{x_i}(1-p_i)^{1-x_i}$$ but what if the trials are not ...
4
votes
3answers
322 views

Is a lower training accuracy possible in overfitting (one class SVM)

I am using the heart_scale data from LibSVM. The original data includes 13 features, but I only used 2 of them in order to plot the distributions in a figure. Instead of training the binary ...