Hey I'm new to Python and I am trying to follow along with a tutorial but I get this error: NameError: name 'tree' is not defined. The objective is obvio
I'd like to use the warm_start parameter to add training data to my random forest classifier. I expected it to be used like this: clf = RandomForestClassifier(
i am running the below code and getting this error. Please help: Error: NameError: name 'predictions' is not defined Code: import pandas as pd import numpy a
I'm trying to import sklearn, however when I attempt to do so I receive the following: ------------------------------------------------------------------------
I am using scikit-learn to implement the Dirichlet Process Gaussian Mixture Model: https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/mixture/dp
I am trying to code a multilayer perceptron in scikit learn 0.18dev using MLPClassifier. I have used the solver lbgfs, however it gives me the warning : Converg
My understanding of "an infinite mixture model with the Dirichlet Process as a prior distribution on the number of clusters" is that the number of clusters is d
I'm trying to understand the relationship between decision_function and predict, which are instance methods of SVC (http://scikit-learn.org/stable/modules/gene
I am plotting a confusion matrix for a multiple labelled data, where labels look like: label1: 1, 0, 0, 0 label2: 0, 1, 0, 0 label3: 0, 0, 1, 0
I am trying to optimize a logistic regression function in scikit-learn by using a cross-validated grid parameter search, but I can't seem to implement it. It
I am performing a grid search to identify the best SVM parameters. I am using ipython and sklearn. The code is slow and runs on only one core. How can this be s
I'm trying to import sklearn model_selection but I'm getting the following error: ImportError Traceback (most recent call last) &