1
vote
1answer
36 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
112 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
155 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 ...
1
vote
0answers
39 views

Heuristic Feature Selection for Gradient Boosting

I originally posted on stackoverflow 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
36 views

error increasing with no of estimators in adaboost

My error gets increased when i increase the n_estimators value in ...
3
votes
2answers
132 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 ...
5
votes
1answer
123 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
72 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
107 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
331 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
160 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
595 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
75 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
185 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
181 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
128 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
65 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? ...
0
votes
1answer
2k 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
424 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
133 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
156 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
264 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
127 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
57 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
117 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
259 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
257 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 ...
9
votes
2answers
2k 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
1answer
171 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 ...
6
votes
2answers
2k 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
254 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 ...
3
votes
2answers
2k views

How to select best parameter for polynomial kernel?

I am using LibSVM library for classification. For my problem I am using polynomial kernel and I need to select best parameters (d = degree of polynomial kernel, and ...
2
votes
2answers
781 views

Collinear variables in Multiclass LDA training

I'm training a Multi-class LDA classifier with 8 classes of data. While performing training, I get a warning of: "Variables are collinear" I'm getting a training accuracy of over 90%. I'm using ...
0
votes
0answers
450 views

Multi Class vs 2 class Naive Bayes

I was wondering what are the implications of using a multi-class Naive Bayes versus a 2 class Naive Bayes (for one against everything). Which technique performs better? I've previously came across ...
3
votes
2answers
505 views

Using Python for building machine learning application

I'm currently using R to find the best approach to solving a machine learning problem. Once I've got the approach sorted, I will need to build this into an application which can be used by end users. ...
0
votes
1answer
244 views

SVM options in scikit-learn

Just curious about two options in the scikits SVM class. Does anyone know what Scale C and shrinking do? Not much in the documentation unfortunately. Thanks
5
votes
1answer
755 views

TF-IDF cutoff percentage for tweets

I'm currently trying to analyze Tweets and classify them as either positive, negative, or neutral using the NLTK library in Python. I can see that there's potential in the approach that I'm taking, ...
6
votes
3answers
1k views

Are there any tutorials on Bayesian probability theory or graphical models by example?

I've seen references to learning Bayesian probability theory in R, and I was wondering if there is more like this, perhaps specifically in Python? Geared towards learning Bayesian probability theory, ...
8
votes
4answers
2k views

What programming language do you recommend to prototype a machine learning problem?

Currently working in Octave, but due to the poor documentation progress is very slow. What language is easy to learn and use, and well documented to solve machine learning problems? I am looking to ...
6
votes
1answer
342 views

Gibbs sampling for a simple linear model — need help with the likelihood function

So in order to better acquaint myself with Gibbs sampling, I've been working on a fairly simple linear model, written in Python/R. Basically, I have 2-dimensional input data (the xi) and a scalar ...
37
votes
8answers
9k views

Machine Learning using Python

I am considering using Python libraries for doing my Machine Learning experiments. Thus far, I had been relying on WEKA but have been pretty dissatisfied on the whole. This is primarily because I have ...