Machine learning framework for Python.

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Various methods for predicting multiple dependent variables (python)

I would like to model and predict multiple dependent variables depending on one or more independent variables. The most straightforward method appears to be multivariate regression. I was wondering ...
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27 views

regression with scikit-learn with multiple outputs, svr or gbm possible?

I have been trying regression with scikit-learn with a problem with multiple outputs like this: ...
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2answers
18 views

What is “Verbose” in scikit-learn package of Python?

What is "Verbose" in scikit-learn package of Python? In some models like neural network and svm we can set it's value to true. This is the documentation: verbose ...
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38 views

Best supervised neural network package for python

What is the best supervised neural network package for python? I found that sci-kit package only have unsupervised neural network.
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33 views

GridSearchCV Regression vs Linear Regression vs Stats.model OLS

I am trying to build multiple linear regression model with 3 different method and I am getting different results for each one. I think that I have to get the same results but ...
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20 views

Normalize time series data - Wikipedia article counts

I have: 3 wikipedia article access counts (weekly) (A-B-C) Ground truth data (weekly) Total wikipedia english article traffic counts (weekly) My purpose is, build a multiple linear regression ...
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1answer
57 views

Text analysis : What after term-document matrix?

I am trying to build predictive models from text data. I built document-term matrix from the text data (unigram and bigram) and built different types of models on that (like svm, random forest, ...
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18 views

When used for feature selection, does the chi-squared test require the features to be nonnegative?

scikit-learn says chi squared test used for feature selection in classification problems and implemented by sklearn.feature_selection.chi2 requires the feature ...
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1answer
37 views

Extremly poor polynomial fitting with SVR in sklearn

I try to fit an obvious around degree 5 polynomial function. Much to my despair, sklearn bluntly refuses to match the polynomial, and instead output a 0-degree like ...
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15 views

Interpret F values of selected features

I have a dataset that contains wines and their ratings. An entry contains the name of the wine, the grapes used, the year and the rating: 'Chateau Pape', 'Pinot Gris', '1983', 93.4 I'm interested in ...
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2answers
27 views

Specify fake-numerical categorical feature to Random Forest?

Suppose I have a mixture of some categorical features and numerically continuous features. I would like to train a classifier based on the features by RandomForestClassifier() in SciKi Learn. Random ...
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21 views

Manually adjusting (stretching) a random forest regressor model

So I have a random forest model (sklearn) fitted to about 3000 data points. It has a poor OOB score (0.3) but it's not completely surprising due to the data set being social media based. The ...
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30 views

What kind of feature selection can Chi square test be used for?

Here I am asking about what others commonly do to use chi squared test for feature selection wrt outcome in supervised learning. If I understand correctly, do they test the independence between ...
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what's the implementation of SciKit-Learn K-Means for empty clusters?

SciKit-Learn's K-Means doesn't discard empty clusters (code of particular function here). Instead, it looks for the pattern that is furthest away from its assigned centroid (assigned cluster but I ...
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1answer
74 views

Why am I getting 100% accuracy for SVM and Decision Tree (scikit)

I have a dataset with 1175 examples and 21 features which are in the range of [-1, +1], and two class labels 1 and 0. As I read in the most of the resources, it is good to have data in the range of ...
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1answer
36 views

Choosing right range for data while using scikit-learn

I have a dataset with 1175 examples and 21 features which are in the range of [-1, +1], and two class labels 1 and 0. As I read in the most of the resources, it is good to have data in the range of ...
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2answers
36 views

Multiple regression/correlation analysis, large dataset:ways, tools [closed]

I've got a large "clean" dataset (800 MB), containing 210k rows and 320 columns. There is 2 discrete string-type columns, others are numeric. One of such numeric columns is selected as depended ...
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2answers
92 views

Classifer for unbalanced dataset?

Is there any classifer that can natively support unbalanced datasets? Or what best practices you can suggest to handle such datasets? For example I want to solve task called "pedestrian detection" ...
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50 views

Obtaining a HOG feature vector for implementation in SVM in Python

I am new to sci-kit learn. I have viewed the online tutorials but they all seem to leverage existing data (e.g., digits, iris, etc). I need the information on how to process images so that they can ...
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2answers
104 views

Treating missing data in voting pattern analysis

I'm trying to analyze voting patterns of Ukraine's parliament deputies. I scraped all the data on their voting during last session. Each data entry has following information: Deputy name, date, bill ...
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28 views

k-fold on dataset

I have been doing a specific check of k-fold technique to see the difference using different number of folds and the corresponding result on the score obtained. To perform this test I have made ...
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10 views

How to perform pattern identification using ML?

I have the following problem: An event, takes place at a determined day of the week, hour, and with a pre-defined format (movie, music concert, lecture (3 items). Based on exit polls we determine 3 ...
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25 views

What will be the simple interpretation for the coefficients for features obtained in any Machine learning models?

I am working with a data that consists of two classes. I have used scikit learn, to craete models using SVM, Randomforest etc.I used to r2_score and I sorted the scores for features I am having and I ...
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18 views

Why does scikit-learn limit the regularization values for its SGD implementation?

The change was made by Olivier Grisel back in 2014 and can be seen here. The first change limits the loss derivatives when they become too big, which makes sense to avoid divergence and numerical ...
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3answers
114 views

Compare performance of 2 models

I have a dataset which I have split into 3 parts: a training set, a cross-validation set and a test set. I have used the training set and cross-validation set to train 2 models. For this, I have taken ...
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20 views

K-cross validation and Naive Bayes

I am doing an exercise of machine learning, and I have built a Gaussian Naive Bayes classifier (i.e., I have defined values of mean and standard deviation) using scikit-learn. Now I am supposed to ...
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1answer
75 views

Difference between statsmodel OLS and scikit linear regression

I have a question about two different methods from different libraries which seems doing same job. I am trying to make linear regression model. Here is the code which I using statsmodel library with ...
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1answer
40 views

Which one is faster? MATLAB SVM or scikit SVM? [closed]

Which one is faster, SVM from MATLAB or SVM from scikitlearn?
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63 views

predict_proba is not available when probability=False

I' m trying to use scikit-learn for a classification, I get ...
1
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1answer
36 views

A question about SVM kernels

this is a very basic question about SVM. I was using SVMs that are provided in the scikit for some problems, and noted that they are quite slow for big datasets. I then learned more about the ...
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1answer
94 views

Plotting learning curves for any classification algorithm

As recommended by Andrew Ng in his great course on machine learning, I would like to plot the learning curves for experiments I am running with Random Forest and SVM algorithms. The learning curves ...
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20 views

feature slection in random forest in python

I have a dataset consisting of 24 numeric features and about 7000 rows, i am applying random forest to get the binary classification, So please tell me how to find only the relevant features to get ...
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27 views

GradientBoostClassifier(sklearn) takes very long time to train

I'm using dataset with 61879 datapoints and 102 features. On this dataset Randomforest(sklearn) takes less than 90s to train for 100 estimators while GradientBoostClassifier(sklearn) is taking forever ...
2
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1answer
68 views

How does Scikit Learn resolve ties in the KNN classification?

I have a multi-class classification problem, in which I'm using Scikit Learn's k nearest neighbour classifier, (5 classes), which means that an odd number for k won't prevent classification ties. So ...
2
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2answers
202 views

Applying PCA to test data for classification purposes

I've recently learned about the wonderful PCA and I've done the example outlined in scikit-learn documentation. I am interested to know how I can apply PCA to new data points for classification ...
2
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1answer
93 views

How to increase the performance of random forest classifier?

I have a text classification task. These are the metrics for different languages at present: class1: 0.6823 class2: 0.7450 class3: 0.66 class4: 0.6719 How can I ...
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31 views

Get bagging sets of random forest in scikit-learn

In scikit-learn each tree of a random forest is trained with a set of samples drawn with replacement from the training set. To do some analysis of a trained forest, it would be nice to know, which ...
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43 views

Balancing Per-Class Accuracy of Multiclass Classifier

Suppose I have a multi-class classifier like Naive Bayes, k-Nearest Neighbors, Decision Trees, Random Forest, etc. The classifier maps a feature vector to (let's say) 3 classes: A, B, or C. My ...
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1answer
57 views

How can I implement probability prediction for One vs One classifier specifically in Sklearn?

I am trying to get probability instead of hard prediction by a One vs One classifier. It is not supported by Sklearn implicitly. Is there nay way to implement it by myself? If so please explain? For ...
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1answer
60 views

Meaning of `max_depth` in GradientBoostingClassifier in scikit-learn

when I use the GradientBoostingClassifier from scikit-learn, I find that there is a parameter max_depth to set, which controls the maximum depth of the regression ...
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16 views

How do i get prediction accuracy when testing unknown data on a saved model in Scikit-Learn?

i have a model i have trained for binary classification, i now want to use it to predict unknown class elements. ...
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27 views

Learning Curve Meaning

I have made a learning curve that looks like this: Why wouldn't it be more like both training and cross-validation score begin low and both gradually increase with more samples? Why does one start ...
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20 views

SciKit Learn - Catch local and trend properties in data?

I have a time dependent dataset with 10 independent and 1 dependent variable. I am trying to fit a multiple regression to make continues predictions. Currently i converted the timestamp into multiple ...
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0answers
17 views

scikit learn gaussian mixture conditional distribution

I am using scikit-learn to fit a Gaussian Mixture Model to a dataset. However, I now need to find the distribution conditional on one or more variables and I have not found a way to do that. Can ...
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0answers
38 views

RandomForest Classifier With Very High Success Rate

I'm having a weird problem that may suprise you all. My classification rate is too high on my test set. I'm using scikit-learn packages, and I'm very suspicious of these classification rates, as they ...
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3answers
240 views

Ensemble of different kinds of regressors using scikit-learn (or any other python framework)

I am trying to solve the regression task. I found out that 3 models are working nicely for different subsets of data: LassoLARS, SVR and Gradient Tree Boosting. I noticed that when I make predictions ...
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1answer
35 views

Does mahalanobis() function in covariance estimators (scikit) really assumed centered observations?

I want to test the various covariance estimators implemented in scikit-learn (for outlier detection). Each of these methods implement a mahalanobis(observations) function. The doc says: ...
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0answers
58 views

Is this a correct way to do document classification using topic modeling?

I am using LDA to extract topics. I want to do topic modelling and use the topics as features to do document classification. I am proposing the below approaches using scikit-learn. I want to know ...
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20 views

What is the fastest way to get the document term matrix in scikit learn?

I am using scikit learn CountVectorizer on top of ~11K documents, each of size ~5000 words. It takes ~ 1 hour to generate the tdm (document term matrix). Is there a much faster way to generate the ...
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sklearn - Multinomial Naive Bayes (data too big???!!!)

I wanted to really understand the rationale behind the following code as written in python sklearn's manual partial_fit(X, y, classes=None, sample_weight=None) when the data is too big to fit in ...