0
votes
1answer
14 views

Feature selection with a binary dependent variable

Given we have a binary dependent variable and 100s of features and ~50k observations, is there a generally accepted way to trim the features via some type of machine learning concept? I was trying a ...
0
votes
1answer
71 views

Calculating the information gain on the features with python

I'm looking for a python library that computes the information gain for the features given a training matrix. Are you aware of any?
0
votes
1answer
35 views

How to get both MSE and R2 from a sklearn GridSearchCV?

I can use a GridSearchCV on a pipeline and specify scoring to either be 'MSE' or 'R2'. I can then access ...
3
votes
1answer
102 views

Training a Tic Tac Toe brain - am I on the right track?

My only experience with Machine Learning is Andrew Ng's Coursera course, but I did work through that just fine and passed with 100%. I decided to practice by making up some problems and solving them. ...
0
votes
0answers
15 views

Turning MiniBatchKMeans into Fuzzy MiniBatchKMeans

I'm using Scikit-Learn, which has an implementation of MiniBatchKMeans. I'm very inexperienced with ML, so I'm wondering how (if ...
2
votes
1answer
62 views

How to prepare interactions of categorical variables in scikit-learn?

What is the best way to prepare interactions of categorical features before fitting with scikit-learn? With statsmodels I could conveniently say in R-style ...
1
vote
1answer
176 views

What is the Probability Distribution of NLTK Naive Bayes?

As I know Naïve Bayes has various distributions, as said in Sci-kit learn manual: The different naive Bayes classifiers differ mainly by the assumptions they make regarding the distribution of ...
0
votes
1answer
57 views

Random forest ML algorithm suitable for use on cluster based HPC?

I have developed a script using pythons scipy package to analyse a rather large model that I wish to solve, the model contains over 12gb of data, including over 500 parameters. Now running small ...
1
vote
3answers
250 views

Complete machine learning library for Java/Scala

Python is plenty of ML libraries (like the great scikit-learn). Is there any good for java/scala, containing many algos (regression, classification, clustering, cross-validation, feature processing), ...
0
votes
0answers
42 views

Build corpus with phrases

I have my documents as: doc1 = beautifull, very good, very bad, you are great doc2 = very bad, good restaurent, nice place to visit I want to make my corpus ...
0
votes
1answer
49 views

A way to use GPU hardware in matlab [closed]

I know that theano is a python library for using gpu hardware and make effective implementations. Is there any such library or a way to do the same in matlab?
0
votes
0answers
88 views

Difference in values of tf-idf matrix using scikit-learn and hand calculation

I am playing with scikit-learn to find the tf-idf values. I have a set of documents like: ...
2
votes
1answer
139 views

Predictive Modeler: How can learning Python and/or Java benefit me?

On a daily basis, I build predictive models (namely, logistic regression and credit scorecard models) using fairly large datasets (typically ~500k records and ~1k candidate variables) to predict ...
2
votes
0answers
55 views

Emotion recognition lip zone processing

I want to detect emotions by comparing the cropped lip zone with different templates and output an emotion based on the score. So far I've applied: Normalization Discrete and fast Fourier transform ...
1
vote
1answer
107 views

Create a matrix of tf-idf values from documents

I have a set of documents like: D1 = "The sky is blue." D2 = "The sun is bright." D3 = "The sun in the sky is bright." and a ...
0
votes
3answers
152 views

Neural network packages which allow shared weights and parallel training

I'm curious if there are any neural network packages out there that easily allow one to construct feed forward neural networks with shared weights, but also allow for the training to be done in ...
10
votes
1answer
605 views

How to split the dataset for cross validation, learning curve, and final evaluation?

What is an appropriate strategy for splitting the dataset? I ask for feedback on the following approach (not on the individual parameters like test_size or ...
1
vote
1answer
67 views

How to initiate bias node in a restricted Boltzman machine

I am new to Neural Networks and trying to implement RBM. I am stuck on initializing the visible layer's bias value. Is it supposed to initialize to some random number or there is some probabilistic ...
0
votes
1answer
325 views

Multidimensional scaling using Python

I have 6,000 points for which I have all pairwise distances in a distance matrix. I want to get an idea whether these data were generated by a mixture of Gaussian distributions so I'm trying to get a ...
0
votes
1answer
222 views

Beginner - How can I use ranked values in my Logistic Regression?

I am running a Logistic Regression on some data to predict if a webpage is "good" or "bad". I got the dataset from a finished Kaggle competiton here (train.tsv). I extract the second column of this ...
2
votes
2answers
140 views

Heuristic Feature Selection for Gradient Boosting

I originally posted on Stack Overflow and was told to move it here. If I am trying to select from two different sets of features for a Gradient Boosting Machine, but I do not want to run through ...
0
votes
1answer
62 views

error increasing with no of estimators in adaboost

My error gets increased when i increase the n_estimators value in ...
3
votes
2answers
268 views

Is it possible to train a one-class SVM to have zero training error?

I'm trying to work on an anomaly detection problem, so I am currently exploring my options on which algorithm is best to use for me. I've been looking at the one-class SVM in the scikit-learn library ...
6
votes
1answer
140 views

Minimizing number of questions of questionnaire from past binary responses

We have data from 600,000 users that describes whether they observe each of 80+ binary features. That is, our data are a 600,000 x 80 binary matrix with user-profile. We know from inspection that ...
0
votes
2answers
89 views

How to find parameters in multivariate space efficiently?

I am trying to optimize sklearn.linear_model.SGDRegressor, and I was wondering if people could point me in which direction I should try to optimize? Personal experience and literature are both ...
0
votes
1answer
171 views

How do you do time series cross-validation using python? [closed]

Also, any tutorials/blogs available that you are aware of?
1
vote
1answer
1k views

Correct use of cross validation in LibsSVM

I am classifying data points from two different groups using LibSVM. I do the following: Creating the input file for LibSVM. ...
0
votes
1answer
339 views

Search in TF-IDF

I want to find the similarity between a document with documents coded as TF-IDF in a pickle file (Python). TF-IDF is done as offline so there is no problem, but when I send a new document for ...
0
votes
1answer
1k views

Decision boundary plot for a perceptron

I am trying to plot the decision boundary of a perceptron algorithm and am really confused about a few things. My input instances are in the form [(x1,x2),target_Value], basically a 2-d input instance ...
1
vote
1answer
85 views

Interpretation of PCA Report from Machine Learning Toolkit

I am using a Machine Learning package called Orange. This software provides a Python interface and a visual programming GUI. I am using the GUI at present. There were 48 original variables. I have ...
2
votes
0answers
215 views

What is a recommended Python framework for Bayes Nets [closed]

What is a good Python framework to use for statistical analysis using Bayes Nets. The following statistical frameworks in one way or other do not support expected features. Python Scikit does not ...
2
votes
2answers
200 views

Fast algorithms to train a perceptron / neural network / ANN

Can anyone provide a brief overview of the most popular training algorithms for perceptrons? I am currently training my perceptron using standard stochastic gradient descent (online gradient descent) ...
2
votes
1answer
157 views

Hierarchical classification where leaf nodes in a tree are at no particular level

I have a set of hierarchical classes (ex. "object/architecture/building/residential building/house/farmhouse"), and I build a tree where each node is a classifier. However, the appropriate class for a ...
0
votes
1answer
71 views

Learning from one positive

Say that in a binary classification problem you have several negatives and only one positive. What types of models are good to learn from this data, and predict the label for a new instance? ...
2
votes
1answer
4k views

libsvm data format

I'm using the libsvm (http://www.csie.ntu.edu.tw/~cjlin/libsvm/) tool for support vector classification. However, I'm confused about the format of the input data. From the README: The format of ...
1
vote
3answers
700 views

Having trouble understanding cross-validation results from scikit-learn

Actually, my question may just be about cross-validation in general. Here's what I'm doing: I'm trying to come up with a model using scikit-learn to learn on some data I've got. I've decided to use an ...
1
vote
1answer
142 views

How to handle Regression data thats not linear

I'm new to stats and am using Python 2.7 to fit a regression model (Random Forest). When I plot the percentile plot of the prices before and after a log ...
2
votes
1answer
165 views

When to Log/Exp your Variables when performing Linear Regression?

I'm doing regression using Random Forests for predicting prices based on several attributes. Code is written in Python using Scikit-learn. How do you decide whether you should transform your ...
3
votes
2answers
370 views

Why is Hedonic Regression used instead of Linear Regression

Why is Hedonic Regression used (especially in housing prices) instead of Linear Regression? There do not seem to be any libraries in Python (and R) for Hedonic regression, is it too niched a ...
6
votes
0answers
208 views

Link Anomaly Detection in Temporal Network

I came across this paper that uses link anomaly detection to predict trending topics, and I found it incredibly intriguing: The paper is "Discovering Emerging Topics in Social Streams via Link Anomaly ...
2
votes
0answers
60 views

How should I distribute a classifier to customers?

When consulting, I often do my exploratory analysis and prototyping in R, and deliver results on the initial dataset to the client. The client wants to use the trained classifier in a production ...
2
votes
0answers
132 views

detecting circadian rhythm in a time series

I have a sensor that can detect minute changes in distance. It produces a time series. I would like to point it at people and detect things like their sleeping pattern. How would one build a system ...
2
votes
1answer
322 views

Simple text classifier: classification taking forever?

I work for a small tech startup, and I want to classify or users into demographics based on the domain of their email address. When users sign up to our site, they can enter a job category, or pick ...
2
votes
1answer
333 views

Simple machine learning: bot detection

I've been aching to get my feet wet with a machine learning project, and I've found one that should be relatively simple, and actually has non-negligible business value for my organization. The ...
12
votes
2answers
4k views

Pandas / Statsmodel / Scikits-learn

Are Pandas, Statsmodels and scikits-learn different implementations of machine learning/statistical operations, or are these complementary to one another? Which of these has the most comprehensive ...
8
votes
1answer
3k views

R vs Python for Data Analysis [duplicate]

Possible Duplicate: Python as a statistics workbench I am just starting out with data analysis and machine learning. From the books that I am reading/have read Python and R seem to be the ...
3
votes
2answers
227 views

Practical applications of affinity propagation

I am learning about machine learning here. They took a set of prices for specific companies on the stock market and graphed them: I would like to know what are some practical applications of ...
8
votes
3answers
3k views

Implementation of CRF in python

Is there a popular implementation of Conditional Random Fields in Python? I can't seem to find any that is widely used and popular!
8
votes
4answers
2k views

Resources for learning how to implement ensemble methods

I understand theoretically (sort of) how they would work, but am not sure how to go about actually making use an ensemble method (such as voting, weighted mixtures, etc.). What are good resources ...
9
votes
3answers
281 views

What is the most efficient way of training data using least memory?

This is my training data: 200,000 Examples x 10,000 Features. So my training data matrix is - 200,000 x 10,000. I managed to save this in a flat file without having memory issues by saving every ...