scikit-learn is a machine-learning library for Python that provides simple and efficient tools for data analysis and data mining, with a focus on machine learning.
I have been using the scikit-learn library. I'm trying to use the Gaussian Naive Bayes Module under the scikit-learn library …
python python-2.7 scikit-learnI need to fit RandomForestRegressor from sklearn.ensemble. forest = ensemble.RandomForestRegressor(**RF_tuned_parameters) model = forest.fit(train_fold, train_…
python pandas numpy scikit-learnI need to split my data into a training set (75%) and test set (25%). I currently do that with the code …
python scikit-learnI have a (26424 x 144) array and I want to perform PCA over it using Python. However, there is no particular …
python scikit-learn pcaI am trying to use train_test_split from package scikit Learn, but I am having trouble with parameter stratify. …
split scikit-learn training-data test-dataI'm using linear_model.LinearRegression from scikit-learn as a predictive model. It works and it's perfect. I have a problem …
python machine-learning scikit-learn linear-regression predictionHow do I save a trained Naive Bayes classifier to disk and use it to predict data? I have the …
python machine-learning scikit-learn classificationI'm facing this error for multiple variables even treating missing values. For example: le = preprocessing.LabelEncoder() categorical = list(df.select_…
python pandas scikit-learnI am trying to design a simple Decision Tree using scikit-learn in Python (I am using Anaconda's Ipython Notebook with …
python scikit-learn visualization decision-treeCan anyone tell me why we set random state to zero in splitting train and test set. X_train, X_…
python random machine-learning scikit-learn