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Art Munson

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Which modeling steps are most important / difficult?

Apr 09 '12 at 11:10 Art Munson646●1●13●16

applications survey data-mining machine-learning

31 Answers

What's the correct way to calculate information gain ratio?

Sparse Features modeling with a Mixture of Gaussians

Platt Calibration w/o Boosting

binning fractional features for classification

ROC curve from the result of a classification or clustering

Classifier sensitivity to combination of categorical and numerical data

'Good' cost values SVM

Difference between linear regression prediction intervals and logistic regression probabilities

large-scale learning of a single decision tree on a single core

genetic programming vs genetic algorithms

A grad student level Machine Learning Outline

sampling for manual evaluation of classification results

Computationally efficient histogram approximations

What are the largest publicly available labeled classification datasets?

Confidence interval for the mean of means

What method can determine the "genetic" origin (mix of sources) of a document?

Measuring quality of unsupervised feature extraction

Using a histogram to estimate class label densities in a decision tree learner

Ensemble Learning Methods

Idiot-proof Machine Learning Methods

MCMC sampling of decision tree space (vs random forests)

Techniques for mapping across two corpora?

Computing inter-annotator agreement for multi-label data?

Running RF using 65000 features

Schedule Forecasting

fast inference in random forests?

Random forest output: Which features are predictive of class?

job prospects in machine learning/data mining

bagging or boosting

Comparing Classifiers Scores

View all questions answered by Art Munson

137 Votes

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50 Tags

machine-learning × 10
classification × 9
data-mining × 8
survey × 7
applications × 7
decision-trees × 6
random-forests × 5
clustering × 3
confidence × 3
sampling × 3

prediction × 3
bayesian × 3
bagging × 2
crossvalidation × 2
data × 2
categorical × 2
statistics × 2
genetic × 2
svm × 2
evaluation × 2

neural-networks × 2
learning × 2
feature-extraction × 2
boosting × 2
semi-supervised × 2
mixture × 2
regression × 2
scoring × 2
feature-learning × 1
dataset × 1

monte-carlo × 1
courses × 1
parameters × 1
training × 1
gradient-descent × 1
ml × 1
precondition × 1
python × 1
interpretability × 1
natural-language-processing × 1

text × 1
forecasting × 1
mcmc × 1
probability × 1
noise × 1
false-positives × 1
naivebayes × 1
labeled-data × 1
early-stopping × 1
unsupervised-learning × 1

15 Kudos

● Appreciated Answer × 10
● Revisitation × 3
● Cognoscenti × 3
● Esteemed Answer × 3
● Prized Question × 1
● Inquisitive × 1

● Guide × 1
● Well-Known Question × 1
● Conspicuous Question × 1
● Commentator × 1
● Participant × 1
● Revisionist × 1

● Mentor × 1
● Advocate × 1
● Prominent Question × 1

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