I am trying to implement bag of word model from kaggle site with a twitter sentiments data which has around 1M raw. I already clean it but in last part when I applied my features vectors and sentim...

I have 7 classes and the total number of records are 115 and I wanted to run Random Forest model over this data. But as the data is not enough to get a high accuracy. So i wanted to apply oversampl...

I understand that random_state is used in various sklearn algorithms to break tie between different predictors (trees) with same metric value (say for example in GradientBoosting). But the document...

Is there a way to retrieve the list of feature names used for training of a classifier, once it has been trained with the fit method? I would like to get this information before applying to unseen ...

I apply the decision tree classifier and the random forest classifier to my data with the following code: def decision_tree(train_X, train_Y, test_X, test_Y): clf = tree.DecisionTreeClassifier()...

I want to plot a decision tree of a random forest. So, i create the following code: clf = RandomForestClassifier(n_estimators=100) import pydotplus import six from sklearn import tree dotfile = six...

Given is a simple CSV file: A,B,C Hello,Hi,0 Hola,Bueno,1 Obviously the real dataset is far more complex than this, but this one reproduces the error. I'm attempting to build a random forest cla...

I am trying to build a model in R with random forest classification. (By editing the code by Ned Horning) I first used randomForest package but then found ranger, which promises faster calculations...

The label in my data is a (N by 1) vector. The label values are either 0 for negative samples or 1 for positive samples (so, it's a binary classification problem). I use the .fit function of sklear...

I am using scikit-learn's Random Forest Regressor to fit a random forest regressor on a dataset. Is it possible to interpret the output in a format where I can then implement the model fit without ...

Is it possible to train a model by xgboost that has multiple continuous outputs (multi-regression)? What would be the objective of training such a model? Thanks in advance for any suggestions

I am trying to plot SHAP This is my code rnd_clf is a RandomForestClassifier: import shap explainer = shap.TreeExplainer(rnd_clf) shap_values = explainer.shap_values(X) shap.summary_plot(shap_va...

There is absolutely helpful class GridSearchCV in scikit-learn to do grid search and cross validation, but I don't want to do cross validataion. I want to do grid search without cross validation an...

I'm learning machine learning in R and making a decision tree in R of expired products, where i have the following data: Product, Category, Temperature, Expire_Day, Rotation_Day, Weight, State Tapa...

Can I extract the underlying decision-rules (or 'decision paths') from a trained tree in a decision tree as a textual list? Something like: if A>0.4 then if B<0.2 then if C>0.8 then class=...

I want to improve the parameters of this GridSearchCV for a Random Forest Regressor. def Grid_Search_CV_RFR(X_train, y_train): from sklearn.model_selection import GridSearchCV from sklearn.model...

Say I have a categorical feature, color, which takes the values ['red', 'blue', 'green', 'orange'], and I want to use it to predict something in a random forest. If I one-hot encode it (i.e. I ch...

I have an imbalanced dataset containing a binary classification problem. I have built Random Forest Classifier and used k-fold cross-validation with 10 folds. kfold = model_selection.KFold(n_splits...

If we serialize randomforest model using joblib on a 64-bit machine, and then unpack on a 32-bit machine, there is an exception: ValueError: Buffer dtype mismatch, expected 'SIZE_t' but got 'long ...

I am attempting to use Random Forest. The training data has 7000 observations with 12 variables. These variables include both categorical and continuous variables. When I submit the code I receive ...

I'm relatively new to Python and am trying to get some data prepped to train a RandomForest. For various reasons, we want the data to be discrete, so there are a few continuous variables that need ...

I have a few questions concerning Randomized grid search in a Random Forest Regression Model. My parameter grid looks like this: random_grid = {'bootstrap': [True, False], 'max_depth': [10, 20, 3...

I'm trying to use GridSearchCV for RandomForestRegressor, but always get ValueError: Found array with dim 100. Expected 500. Consider this toy example: import numpy as np from sklearn import ense...

In sci-kit learn, it's possible to access the entire tree structure, that is, each node of the tree. This allows to explore the attributes used at each split of the tree and which values are used f...

For the code given below, I am getting different bar plots for the shap values. In this example, I have a dataset of 1000 train samples with 9 classes and 500 test samples. I then use the random fo...