Machine learning framework for Python.

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Dealing with numbers-based categorial data in rf regression: to standardize, or encode?

I'm working with the SEER cancer dataset, and I'm trying to use regression to calculate the months a breast cancer patient can expect to survive given certain variables. Some of these variables are ...
4
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1answer
65 views

How to apply a Gaussian radial basis function kernel PCA to nonlinear data?

I have an assignment to implement a Gaussian radial basis function-kernel principal component analysis (RBF-kernel PCA) and have some challenges here. It would be great if someone could point me to ...
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1answer
17 views

Generating even-sized clusters in scikit-learn [duplicate]

I'm attempting to generate approximately even-sized clusters of a PCA'd feature set in Scikit-learn, but I'm not having any luck. I'm only familiar with KMeans clustering, and with that algorithm the ...
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18 views

Naive Bayes and text classification: which probability model and vectorizer combination makes sense?

I am wondering which combinations of Naive models can be paired with different vectorizing methods so that it makes sense. Let's say we have a simple binary spam-classification task. Multinomial ...
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1answer
46 views

Excluding the scatter points from a feature

I have a set of data points that are supposed to sit on a locus and follow a pattern, but there are some scatter points from the main locus that cause uncertainty in my final analysis. I would like to ...
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1answer
49 views

classification algorithms that return confidences?

Given a machine learning model built on top of scikit-learn, how can I classify new instances but then choose only those with the highest confidence? How do we define confidence in machine learning ...
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79 views

Why does the scikit-learn bootstrap function resample the test set?

When using bootstrapping for model evaluation, I always thought the out-of-bag samples were directly used as a test set. However, this appears not to be the case for the scikit-learn bootstrap ...
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0answers
15 views

How could I generate an “explanation” for each prediction in a classification ?

I have a classification problem. My classes are 0 and 1. The dataset is a bit big, the training is done on 7 million lines and 100 + variables so I choose to use scikit learn and the logistic ...
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20 views

why is adaboost predicting probabilities with so little standard deviation?

I'm using several algorithms to predict a binary target. So far I tried Gradient Boosting, Random Forest, Extra Random Trees and adaboost from scikit learn. All of these algorithms appear to predict ...
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1answer
34 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 ...
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17 views

Joint label between two datasets produces significantly worse results

I have two sets of corresponding example labels with more or less the same features. Let's call first one label A and the second one label B. Both labels are binary. The classification accuracy of ...
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3answers
314 views

Why Python's scikit-learn LDA results are different from LDA in R or a step-by-step approach

I was using the Linear Discriminant Analysis (LDA) from the scikit-learn machine learning library (Python) for dimensionality reduction and was a little bit curious about the results. I am wondering ...
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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. ...
3
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1answer
41 views

K-means metrics

I have read through the scikit learn documentation and Googled to no avail. I have 2000 data sets, clustered as the picture shows. Some of the clusters, as shown, are wrong, here the red cluster. I ...
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1answer
44 views

How to deal with a skewed class in binary classification having many features?

I am doing data analysis in the mobile ad targeting domain. I have around 18 features and for a combination of these features, the result is either True or False (1/0) depending on whether the ...
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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 ...
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0answers
58 views

Running R caret in Python script [closed]

I am currently trying to transition from R into Python to streamline the process of working in web-based applications. I know that SciKit Learn has a ton of functionalities parallel to R's, including ...
2
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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 ...
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54 views

How to prepare data for classifiaction

I have a relative small dataset that is consisted of numerical, nominal as well as text features. Some cells are empty whereas the class type is nominal and can take any of the ~10 different ...
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3answers
168 views

Naive Bayes: Imbalanced Dataset in Real-time Scenario

I am using scikit-learn Multinomial Naive Bayes classifier for binary text classification (classifier tells me whether the document belongs to the category X or not). I use a balanced dataset to train ...
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1answer
31 views

document similarity with documents using synonyms

I have a bunch of documents where some of the documents are a copy of other documents with their text jumbled up and some of the words replaced by their synonyms. Mentioned below is one such example ...
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2answers
129 views

Use of nested cross-validation

Scikit Learn's page on Model Selection mentions the use of nested cross-validation: ...
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0answers
35 views

Gaussian Mixture Model - Density estimation

I am working on the estimation of density function and I am using the scikit-learn library. As example of code I am looking at the code at the following link. My doubt is at this following line of ...
3
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1answer
83 views

Clustering without a distance matrix

I've recently completed a project where I used scikit-learn's DBSCAN module to find clusters in relatively short strings of text. I used a custom string similarity ...
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95 views

Possible to evaluate GLM in Python/scikit-learn using the Poisson, Gamma, or Tweedie distributions as the family for the error distribution?

Trying to learn some Python and SKLearn, but for my work I need to run regressions that use error distributions from the Poisson, Gamma, and especially Tweedie families. I don't see anything in the ...
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45 views

What method should I use for this optimization / feature selection project

I'm going to describe a problem and I'm not sure how to best solve it. I will describe the situation. When answering please recommend a method and maybe a software library. I'm using Python for my ...
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32 views

How to enforce periodic boundary conditions when performing regression with sci-kit learn?

I have signals that resemble sine waves (or, more accurately, sums of sines). The data are normalized in the time domain so that there is only one cycle and all of the points lie between 0 and 1. An ...
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36 views

Optimal feature selection for MAPE criteria with RandomForest cross-validation

I am trying to optimize my set of features against random forest cross-validation using MAPE criteria. I tried forward selection with Univariate linear regression test (f_regression in sklearn), I ...
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33 views

Multivariate Multiple Classification

Is it possible to have multiple (at least 3) dependent variables in a single classification model. I know this can be accomplished in a regression model but I need to perform this with a ...
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0answers
27 views

Merging different datasets for binary classification

I have four ($D_1, ... D_4$) different datasets from which I want to learn a robust binary classifier. I am currently using SVC and ...
10
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1answer
597 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 ...
2
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1answer
136 views

Which metric should I trust to evaluate my predictive model

I am working on predictive model and when I evaluate it, I find good accuracy_score, precision_score, ...
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1answer
368 views

How can we evaluate the predicted values using Scikit-Learn

I am using AdaBoost Classifier to predict values I have. How can evaluate the accuracy of prediction model (I'd like to see how the accuracy of predicted values). You can check an example here: ...
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1answer
209 views

How do we use logistic regression (scikit-learn) to predict values

Logistic regression can help to predict a value whether it would happen or no. I'd like to know how can I do that using sklearn. I'd like to know the probability if this event would happen or no. I ...
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1answer
152 views

How do we predict rare events?

I am working on developing an insurance risk predictive model. These models are of "rare events" like airline no-show prediction, hardware fault detection, etc. As I prepared my data set, I tried to ...
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2answers
119 views

Streaming k-means

I want to perform something like streaming/online/out-of-core kmeans clustering on large data. Here is simple idea: Break all data into N chunks. Read from disk 1st chunk and calculate centroids ...
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0answers
39 views

scikit learn: add lasso or ridge penalty only on subset of parameters

Is there a way of using the linear model api to add the lasso penalty for a subset of the parameters I am regressing? For example, consider a linear separable decomposition that I want to fit to some ...
0
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1answer
39 views

R's equivalente of scikit's KFold

I'm new to R and I'm trying to set up a basic k folds CV loop. In Python I'd use scikit's KFold. ...
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0answers
18 views

How Does a Disparity in Number of Documents (Training Data Points) Affect Text Classification?

I have collected a fairly clean set of data (5,410 documents) to train a text classifier. I am now attempting to improve my classification success. (Note: When I trained/tested the classifier from ...
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31 views

Training models for classification using different negative datasets

I'm working on a massively unbalanced binary classification task - Classification of given protein sequences as belonging to a certain (very small) class, or not. There are about 1,300 positive ...
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74 views

“Robust” normalization of features from multiple groups and unknown distributions prior to learning

I'm working on a machine learning project involving statistical analysis (and later discriminatory classification) of different proteins (samples) drawn from multiple, potentially overlapping classes ...
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2answers
180 views

Prediction with scikit and an precomputed kernel (SVM)

I am kind of a newbie in the MachineLearning area and evaluating some tools etc. to get a feeling for it. For a project I am using a tool that creates a precomputed kernel (gram matrix) and also is ...
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1answer
232 views

What is the right attitude toward open source machine learning toolkits?

There are lots of machine learning toolkits nowadays, such as weka, sklearn, R libs. If we choose to use these toolkits, besides that it is convenient, sometimes ...
0
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1answer
44 views

Regression Tree when target is a ratio

I am learning a regression tree for data of the form $(x_i,y_i)$: $x_i = (1, 0, 1, ...., 1 , 1)$ a multiple input vector and $y$ is a ratio of the number of observations divided by the number of ...
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0answers
389 views

Using BIC to estimate the number of k in KMEANS

I am currently trying to compute the BIC for my toy data set (ofc iris (: ). I want to reproduce the results as shown here (Fig. 5). That paper is also my source for the BIC formulas. I have 2 ...
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0answers
35 views

building a feature set for scikit learn

Im using RandomForestClassifier for a probability prediction task. I have a featureset of around 50 features and two possible labels - ...
2
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2answers
527 views

How to compute the standard errors of a logistic regression's coefficients

I am using Python's scikit-learn to train and test a logistic regression. scikit-learn returns the regression's coefficients of the independent variables, but it does not provide the coefficients' ...
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0answers
42 views

Imputing categorical variables before binarization

I wish to replace the missing values with mode of that categorical variable. In scikit-learn, we can something like Imputer(strategy="most_frequent", axis=0) but ...
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0answers
43 views

How to normalize ranked data

I am doing some machine learning and need help with the stats aspect of my problem. I have a number of addresses of webpages and some features for these webpages. I am running TF-IDF on the webpage ...
2
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1answer
109 views

Name of algorithm (or paper) that scikit-learn cluster.estimate_bandwidth() function implements for meanshift bandwidth selection

Can someone tell me the name of the algorithm (or paper) that sklearn.cluster.estimate_bandwidth implements and is used by the meanshift algorithm implemented in Scikit-Learn to automatically select ...