Machine learning framework for Python.

learn more… | top users | synonyms

0
votes
0answers
18 views

Which naive Bayes?

I am attempting to use a naïve Bayes classifier in python (using scikit-learn), with two examples. The first example has 6 classes and 2 hypotheses, the 2nd example has 2 classes and 6 hypotheses. ...
0
votes
0answers
11 views

Make a classification dataset with binary features using scikit-learn

I would like to illustrate a classification algorithm by using this algorithm on a 2-class dataset with binary n-dimensional features. In the past, I have used the scikit function make_classification ...
0
votes
0answers
31 views

How can you print the decision tree of a RandomForestClassifier

Recently, I have noticed that there is a method sklearn.tree.export_graphviz documented here. However, I do not know how I can apply it to a ...
0
votes
0answers
16 views

How do I get a classification report for my cross validated scores using sklean

I am running a logistic regression model using sklearn with 2 classes (1 and 0). Here is my code: ...
0
votes
0answers
16 views

How can I improve my sklearn logistic regression model

My objective is to classify sentences into useful (denote in boolean as 1) and not useful (denote in boolean as 0) categories. I have about 525 features where 300 features are the most frequent and ...
1
vote
1answer
129 views

scikit multi label classification

I am trying to classify data into four different labels. The training data looks something like: ...
0
votes
1answer
27 views

what does the numbers in the classification report of sklearn mean?

I have below an example i pulled from sklearn 's sklearn.metrics.classification_report documentation. What i dont understand is why there are f1-score, precision and recall values for each class ...
1
vote
1answer
19 views

Logistic-Regression: Prior correction at test time

Using sklean.linear_model.LogisticRegression for a binary classification problem. My classes are unbalanced. The positive class comprises about 20% of the training set. When fitting the model I use: ...
0
votes
0answers
14 views

How to scale data to train RBMs?

I know that when training Bernoulli Restricted Boltzmann Machines with real-valued data, then the input data should be scaled to the interval $[0,1]$ (last section from here). What I understood is ...
1
vote
1answer
33 views

Out-Of-Bag estimate in scikit-learn

I am using a bagging model from the Python Scikit-Learn module: ...
0
votes
0answers
42 views

More recognizable Python implementation of Linear Discriminant Analysis?

I have been using scikit-learn's LDA implementation to do some experiments, and recently wanted to test out some modifications to the LDA derivation. I was looking at the Python implementation that ...
1
vote
0answers
18 views

How do I filter insignificant modes from a kernel density estimation

How do I detect the number of significant modes in a set of data? I have a set of 1 dimensional data where the number of modes are unknown. I'm familiar with python and scikit learn so I use the ...
0
votes
0answers
13 views

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
votes
1answer
112 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 ...
0
votes
1answer
19 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 ...
1
vote
0answers
30 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 ...
3
votes
1answer
56 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 ...
1
vote
1answer
66 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 ...
7
votes
0answers
90 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 ...
0
votes
0answers
16 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 ...
0
votes
0answers
24 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 ...
0
votes
1answer
68 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 ...
0
votes
0answers
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 ...
7
votes
3answers
411 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 ...
3
votes
1answer
111 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
votes
1answer
47 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 ...
0
votes
1answer
52 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 ...
0
votes
0answers
19 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 ...
1
vote
0answers
72 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
votes
1answer
76 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 ...
0
votes
0answers
61 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 ...
2
votes
3answers
189 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 ...
0
votes
1answer
34 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 ...
3
votes
2answers
201 views

Use of nested cross-validation

Scikit Learn's page on Model Selection mentions the use of nested cross-validation: ...
0
votes
0answers
38 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
votes
1answer
95 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 ...
1
vote
0answers
118 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 ...
0
votes
0answers
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 ...
1
vote
0answers
36 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 ...
0
votes
0answers
44 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 ...
0
votes
0answers
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 ...
0
votes
0answers
29 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
votes
1answer
876 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
votes
1answer
150 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, ...
1
vote
1answer
471 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: ...
0
votes
1answer
271 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 ...
1
vote
1answer
194 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 ...
0
votes
2answers
133 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 ...
1
vote
0answers
41 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
votes
1answer
46 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. ...