Machine learning framework for Python.

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Scikit Random forest pred_proba gives rounded off values

I am using random forest in scikit learn for classification and for getting the class probabilities , I used pred_proba function. But strangely it outputs probabilities rounded to first decimal place ...
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16 views

SKLearn Clustering: how would you cluster a LARGE database of dogs? [on hold]

Given: A VERY large dataset of dogs. columns: ID (alphanumeric) Weight (numeric) Height (numeric) Eye Color (alphabet) ... (numeric) Tongue Length (numeric) How do you find what makes these ...
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1answer
12 views

Identifying filtered features after feature selection with scikit learn

Here is my Code for feature selection method in Python: ...
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8 views

Are there methods in scikit-learn package for classification of input data based on its sequential relation?

I am sorry if this turns out to be a trivial question, since i am still new in this machine learning field. My question is, are there methods in scikit-learn package for classification of input data ...
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1answer
50 views

Scikit Binomial Deviance Loss Function

This is scikit GradientBoosting's binomial deviance loss function, ...
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22 views

Sensitivity to scaling of multivariate data with HMM

I have some multivariate data, say 40 features. Some features are scaled between 0 and 1, and some are scaled between 0 and 1e8. For reference, I am using sci-kit learn's HMM implementation (yes, I ...
2
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1answer
30 views

Area under Precision-Recall Curve (AUC of PR-curve) and Average Precision (AP)

Is Average Precision (AP) the Area under Precision-Recall Curve (AUC of PR-curve) ? EDIT: here is some comment about difference in PR AUC and AP. The AUC is obtained by trapezoidal ...
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0answers
36 views

Affinity Propagation (sklearn) - strange behavior

Trying to use affinity propagation for a simple clustering task: ...
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1answer
21 views

How to preprocess a large sparse matrix and unbalanced classes in machine learning

I have a large very sparse matrix with 1000 columns and 15000 rows. It mainly contains zeros, the rest is integer values from 1-8. I'm limited to scikit-learn and ...
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1answer
79 views

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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2answers
68 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
31 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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76 views

Time series forecasting using SVM

I am trying to set up a Python code for forecasting a time series, using SVM libraries of scikit-learn. My data contains $X$ values at a day interval for the last one years, and I need to predict $y$ ...
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1answer
81 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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1answer
47 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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0answers
27 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
91 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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22 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
46 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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0answers
20 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
34 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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29 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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0answers
50 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 ...
2
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1answer
32 views

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
87 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
42 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
53 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
131 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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98 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
116 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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31 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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0answers
13 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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28 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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0answers
22 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
116 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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29 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
125 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
46 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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120 views

predict_proba is not available when probability=False

I' m trying to use scikit-learn for a classification, I get ...
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1answer
39 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
126 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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28 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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0answers
30 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
81 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
263 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
148 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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33 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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54 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
78 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
83 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 ...