Machine learning framework for Python.

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Sparse Coding Library example in scikit-learn [migrated]

I just started learning about machine learning and using scikit-learn. But scikit-learn is a little bit difficult for me to use and understand completely what it is doing. So cloud you help me to ...
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21 views

Hierarchical clustering and sklearn [on hold]

I would like to know if there is a reason why in sklearn library is not implemented a partitional solution for hierarchical clustering. I think that is possible to apply recursively a K-means ...
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10 views

Plot the cost function vs. number of iteration [closed]

i want to Plot the cost function vs. Number of iteration on the multivariable dataset by using scikit, I want to know is there any ready library or commands to do that? or anyone has any example for ...
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18 views

plotting SVM in python [closed]

I tried following the example here but i am having trouble applying it when i have 16 features. lin_svc is trained with those 16 features (i deleted the line to ...
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41 views

Causal Trees to Estimate Heterogenous Treatment Effects: Transformed Outcomes [Machine Learning in Python]

I am interested in using off-the-shelf tools like scikit-learn for Python to implement the Athey-Imbens recommendation for estimating treatment effect ...
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1answer
39 views

Linear Ridge not correct prediction/coefficients- Scikit learn

I am using a similar code to this ridge example. The code proposed is simple. X and Y points inside [-1,1] range and predict the radius creating polynomial features and ridge linear regression. As ...
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1answer
20 views

Where can I read about gamma coefficient in SVM in scikit-learn?

Scikit learn support vector machine algorithm have a couple of coefficients which meaning I can not understand. gamma : float, optional (default=0.0) Kernel coefficient for ‘rbf’, ‘poly’ ...
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17 views

How to use RFECV for feature selection and cross validation

I am still very new to machine learning and trying to figure things out myself. I am using SciKit learn and have a data set of tweets with around 20,000 features (n_features=20,000). So far I achieved ...
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2answers
89 views

From where I can learn to use scikit learn

I have read text about machine learning and I feel that I have gained sufficient knowledge that I can start applying them practically. I have programming experience in python so I want to learn how to ...
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324 views

CV (Curriculum Vitae) Recommender system - guidance

Please note that I am a total beginner with machine learning and artificial intelligence and also a novice with Python (I'm sure I have a very non-Pythonic way of writing code). I have a college ...
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9 views

Discrete variables: Gaussian Naive Bayes or Bernoulli Naive Bayes?

I have a dataset of which features are: Hour Weekday Day Month 10 7 30 12 12 3 15 1 ... and with binary labels ...
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14 views

On which kind of problems preprocessing data using RBMs (unsupervised) could give an edge?

I am new to machine learning and basically so far I've been using only supervised algorithms, however, recently I started to use RBMs in combination with some classifier (using a pipeline in scikit ...
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1answer
22 views

Alpha parameter in ridge regression is high

I am using the Ridge linear regression from sickit learn. In the documentation they stated that the alpha parameter has to be small. However I am getting my best model performance at 6060. Am I doing ...
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1answer
23 views

Scikit-learn Scaled Data - Means Not Zero

I tried to scale the data by referring to the link as follow: http://scikit-learn.org/stable/modules/preprocessing.html However, when I checked the data distribution, the mean returned is NOT ZERO. ...
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2answers
132 views

How to standardize the variables in R for regression analysis

I have been looking at some tutorials and articles and couldn't get a scenario where two variables are in different scales and used in modeling. So, firstly lets assume I have one metric of numeric ...
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9 views

How does one call external datasets into scikit-learn? [migrated]

For example consider this dataset : (1) https://archive.ics.uci.edu/ml/machine-learning-databases/annealing/anneal.data or (2) http://data.worldbank.org/topic How does one call such external ...
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9 views

understanding accuracy assessment of classification

I want to classify an image and I want to know how well I did, but I am not sure if I understand the workflow properly. I use scikit-learn. I first use cross_validate and GridSearchCV to find the ...
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28 views

How to add cluster centers to the already transformed arrays with T-SNE Scikit Learn?

let's get this scikit original code, which is basically the one I'm using. My X is 2000x100 and in order to plot the clusters (plot on the right) I want to transform it with with the TSNE algorithm ...
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1answer
38 views

does sklearn rbm scale well with sparse high dimensional features

i am using scikit learn's RBM implementation. There are two problems: The running time is O(d^2) where d is the number of features. This becomes a problem in using high dimensionality sparse ...
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21 views

Feature selection of SVM

My question is three-fold In the context of "Kernelized" support vector machines Is variable/feature selection desirable - especially since we regularize the parameter C to prevent overfitting and ...
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25 views

Pandas generating features vector with apply()

I have a data set with two features: class (int) and content (text). Each row of content needs to be vectorized to a set of boolean features matching regexes. My vectorized function return a ...
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49 views

Did I use gradient descent correctly?

In an attempt to learn Gradient Descent. I've created my own dataset which is a the total bill of a meal with tips. As I created the perfect data so I make every meal with 10% tip. I purposely ...
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1answer
70 views

Can a Precision-Recall curve or a ROC curve be horizontal?

I am working on a binary classification task on imbalanced data. Since the accuracy is not so meaningful in this case. I use Scikit-Learn to compute the Precision-Recall curve and ROC curve in order ...
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20 views

What does it mean if the ROC scores are quite different when using the Stratified K fold with and without shuffling?

I'm currently building a random forest classification and trying to measure the model performance by the [mean ROC area]. With the same data set: When I use cross_validation.StratifiedKFold(y, ...
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1answer
65 views

How can 1 more feature disrupt a Random Forest's confusion matrix?

I'm trying to predict a binary variable with both random forests and logistic regression. I've got unbalanced classes (approx 1.5% of Y=1), so i'm calling ...
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20 views

scikit GBT terminal node updates

I am trying to understand scikit's gradient boosted tree implementation, i struggling to understand the terminal node update part ...
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175 views

What are the differences between Ridge regression using R's glmnet and Python's scikit-learn?

I am going through the LAB section §6.6 on Ridge Regression/Lasso in the book 'An Introduction to Statistical Learning with Applications in R' by James, Witten, Hastie, Tibshirani (2013). More ...
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16 views

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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1answer
60 views
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Identifying filtered features after feature selection with scikit learn

Here is my Code for feature selection method in Python: ...
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22 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
104 views

Scikit Binomial Deviance Loss Function

This is scikit GradientBoosting's binomial deviance loss function, ...
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29 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
102 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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43 views

Affinity Propagation (sklearn) - strange behavior

Trying to use affinity propagation for a simple clustering task: ...
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1answer
30 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
127 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
137 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
65 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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110 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
135 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
81 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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44 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
127 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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24 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
67 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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21 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
46 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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35 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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96 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 ...