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Questions tagged [random-forest]

Random forest is a machine-learning classifier based on choosing random subsets of variables for each tree and using the most frequent tree output as the overall classification.

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Evaluating the test set

Please find attached a part of the code which explains what I'm trying to do. Essentially I'm trying to predict the sales of supermarket stores. Im using RandomForestRegressor for this and have ...
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7 views

Different time duration (block) for a classification model [closed]

Suppose there are 1-5 set of activities that one can complete and #activities that one complete is a predictor variable for event(1 or 0).This set of activities can be completed during any time of ...
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21 views

Dataset where svm performance is significantly different from random forest

Is there a specific dataset where svm performs significantly better or worse than random forest? I know that the performance could depend on the dataset but is there a specific dataset?
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Need help understanding time series approach used for predicting earthquake arrival?

In predicting the arrival time of earthquakes, a paper here seems to make use of a time series approach that is making me scratch my head, and I would appreciate any guidance on understanding it. In ...
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How can I recognise if I can improve a random forest model by adding features

I want to tune a random forest model with caret package. I'm tuning it with cross-validation to prevent overfitting and resulted cross-validation accuracy is very ...
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49 views

Get insights from Random forest::Variable Importance analysis

I run variable importance on my Panel data (TV viewing over specific period) which consists of the old-Panel (Panel 0) and the new panel (Panel 1) I am interested in understanding the differences in ...
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24 views

very low recall value using random forest

I have download this data-set which can be download from here. I have tried everything I can think of, such as one-hot encoding the output, standardisation, removing outliers, remove columns with too ...
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1answer
116 views

Why is performance worse when my time-series data is not shuffled prior to a train/test split vs. when it is shuffled prior to the split?

We are running RandomForest model on a time-series data. The model is run in real time and is refit every time a new row is added. Since it is a timeseries data, we set shuffle to false while ...
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13 views

Get Decision Tree Prediction With Random Forest

If I give random forest parameters as RandomForestClassifier(n_estimators=10,bootstrap=False,max_features=None,random_state=2019) Should it be creating 10 same ...
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17 views

How to encode H3 geohash in regression model

I'm trying to train a random forest regression model based on a number of features, including location. I know that raw lat/long can't be used directly, so I've bucketed them using H3. I'm struggling ...
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33 views

How to deal with count data in random forest

I am working on a classification model where my target class is a biased class with the class shape as 0 1 20694 101 Most of my features are the ...
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1answer
38 views

Is it possible to plot decision boundaries for only a subset of features?

I have a sklearn Random Forest classifier with 59 features as input. I'd like to plot the decision boundaries of only two features at indices i1 i2. If I use the average/median values for the ...
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81 views

Will unnecessary features harm the tree based model?

Is it necessary to drop noisy features (eg column of random numbers) from tree features? I think it's not. sometimes it may benefit but will never cause any harm to the model. Because at each split ...
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9 views

Is it possible to rank feature importance after training a recommender system?

I need to train a recommender system on some movie recommendation data. The thing is, I wanted to use a random forest for the model, since I know you can print a feature hierarchy, after training. I'...
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27 views

Relation between using stratify and class weights for imbalanced classes

I'm working on a multi-class classification problem where the classes are imbalanced (70:25:5). Train-Test Split ...
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0answers
20 views

What is the difference between PySpark's featuresCol, labelCol, predictionCol, and probabilityCol?

I am attempting to train a random forest classifier (pyspark.ml.classification.RandomForestClassifier) on a large dataset (~70gb). However, I am not sure what to ...
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13 views

Insights from RandomForestRegressor (or any RF output)

Beyond the feature importance calculations from a RandomForestRegressor in sklearn, what are some good strategies to draw ...
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2answers
39 views

Classification model for recommender system?

I have some data for various customers choosing one of 'n' products or no product. I have some useful features for each customer. I can build a multi-class classification problem out of this data and ...
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2answers
36 views

how to get prediction from trained random forest model? [closed]

i have a dataset with two columns user posts (posts) and personality type (type) , i need personality type according to posts using this dataset so i used random forest regression for prediction here ...
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28 views

WEKA Random Forest J48 Attribute Importance

I have been using WEKA to classify very long duration audio recordings. The best performing classifiers have been Random Forest and J48. The attributes used to classify the audio are acoustic indices. ...
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Are my Random Forest Classifier and Regressors overfitting?? I have CV and learning curves!

I seem to be getting great results from logistic regression with RFE and random forest feature importances in support, but there's been a suggestion of overfitting and when I run learning curves the ...
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1answer
120 views

Mean Absolute Error in Random Forest Regression

I am new to the whole ML scene and am trying to resolve the Allstate Kaggle challenge to get a better feeling for the Random Forest Regression technique. The challenge is evaluated based on the MAE ...
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Reducing Bias when trying to find Feature Importance using a Random Forest

I'm currently looking to show which of three variables is more important in classifying something as True or False. Everyone agrees that all three variables are important, but not all agreeing on what ...
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1answer
33 views

Who wrote the formula for gini importance/sklearn's feature importance score?

I've been looking for a paper where the Gini importance was first proposed, but I am not sure if this is actually how it came to be. Here's the formula I am familiar with and am looking to find in a ...
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23 views

Misclassification splitting criterion for Random Forest

I would like to use misclassification for the splitting criterion to grow a Random Forest. Is anyone aware of a package, ideally in R or Python, that utilizes this splitting criterion? I've looked ...
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1answer
25 views

Please help select an Algo based on Accuracy and Confusion Matrix

I am very new to Data Science would appreciate your advice big time. Got a task: predict if a trade will be profitable or not, based on a set of data. I have prepared, cleaned and tested data. ...
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Effect of Multiple Columns with same name and different values on Random Forest Classifier

I am new to machine learning. Recently I am working on a project in which I am predicting whether patient would suffer from diabetes or not. I am using Random Forest Classifier from sklearn. I have ...
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How to fit a Random Forest with a very small amount of data?

I am working on a Signal Processing project in the Bio-Medical domain. I have to implement a Random Forest Classifier to classify Lung X-Ray parameters in terms of Tuberculosis. The data is in the ...
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617 views

Should I remove outliers if accuracy and Cross-Validation Score drop after removing them?

I have a binary classification problem, which I am solving using Scikit's RandomForestClassifier. When I plotted the (by far) most important features, as boxplots, to see if I have outliers in them, I ...
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1answer
22 views

Adding variables to Random Forest decreases performance

Let's say you have 6 variables. A Random-Forest regression using the first 5 variables has an R^2 of 0.1. Another regression using just the 6th variable yields R^2 of 0.3. All of the first 5 ...
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43 views

Target transformation for tree models

Can anybody explain why/if target variable transformations could help when dealing with tree based models? I've seen this excellent reply which explains quite well why it shouldn't affect if ...
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1answer
27 views

How can I avoid requiring global information for performing regression on meter variables?

Note: With a meter variable a timestamped value is the sum of all previous differences plus a difference to the most recent value. Think of a electricity meter counting the use of energy. The goal ...
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1answer
48 views

Random Forest, Duplicating Data increases Accuracy. Why? [closed]

I duplicated my training data for the random forest classifier (Sklearn) and the accuracy of the prediction increased by about 3%. Why?
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1answer
15 views

Mixed effect random forest model for Python Windows

Does anybody know if there is a Mixed effect random forest model for Python Windows? The merf package https://anaconda.org/search?q=merf+ seems to only be available on a linux environment? thanks!
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107 views

learning curve Sklearn

I was trying Random Forest Algorithm on Boston dataset to predict the house prices medv with the help of sklearn's RandomForestRegressor. Just to evaluate how good ...
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1answer
84 views

A few questions to understand a random forest blog [closed]

I'm trying to understand a nice blog on the trade-off between sensitivity versus specificity with the random forest and logistic regression models. I have a few questions: 1) The blog used a 10 fold ...
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1answer
34 views

Can random forest algorithm provide customer churn prediction probability at each customer instead at class level?

I have customer training data set from telecom industry along with its test data set containing churn values 0 & 1 for each customer. I also have customer data set whose churn value is to be ...
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1answer
16 views

During a regression task, I am getting low R^2 values, but elementwise difference between test set and prediction values is huge

I am doing a random forest regression on my dataset (which has abut 15 input features and 1 target feature). I am getting a decently low R^2 of <1 for both the train and test sets (please do let me ...
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1answer
29 views

classification of small group

I have a dataset with 106K rows, each row contains 391 features. 1K of the rows are labeled as group 1 and all the others as 0. I want to create a model to classify the small group. Is it possible? ...
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1answer
38 views

Training and Test set

I was asked by my supervisor to replicate a result from a former graduate student. My supervisor believes the result of that paper is not accurate and he asked me to find out why! The paper was about ...
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1answer
53 views

Why xgboost can not deal with this simple sentence case?

There is only 1 feature dim. But the result is unreasonable. The code and data is below. The purpose of the code is to judge whether the two sentences are the same. In fact, the final input to the ...
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3answers
393 views

using sklearn class weight to increase number of positive guesses in extremely unbalanced data set?

Hi I have a poorly correlated and unbalanced data set I have to work with. The set is 2 classes, 0 has 96,000 values and 1 has about 200. When I run random forest or other methods I get an output like:...
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1answer
29 views

Boostrap parameter in random forest regressor?

There's one parameter in RandomForestRegressor which is bootstrap. By default bootstrap=True bootstrap : boolean, optional (...
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1answer
208 views

How to interpret partial dependence interaction plot for binary classification?

The plot below is an example from pdpbox library https://github.com/SauceCat/PDPbox/blob/master/tutorials/pdpbox_binary_classification.ipynb. The what does 0.900 color saturation to the right mean ...
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1answer
52 views

Why would a fake feature with random numbers get selected in feature importance?

I'm using a sklearn.ensemble.RandomForestClassifier(n_estimators=100) to work on this challenge: https://kaggle.com/c/two-sigma-financial-news I've plotted my ...
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3answers
53 views

Using deep learning or random forest [closed]

I am very new to machine learning, and I am trying to build a model to classify this data set (UCI heart disease). I have built a simple model using random forest and got an 80% accuracy. The size of ...
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4answers
361 views

Exceptionally high accuracy with Random Forest, is it possible?

I need your help to find a flaw in my model, since it's accuracy (95%) is not realistic. I'm working on a classification problem using Randomforest, with around 2500 positive case and 15000 negative ...
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0answers
11 views

Efficient Similarity Indexing and Searching in High Dimensions

I found this recent document, containing simple algorithm that properly indexes high dimensional vectors for binary search later. Algorithm basically uses random partition forest that randomly ...
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1answer
30 views

Explaination of the anomalies detected

I have a dataset with a mixture of categorical and numeric variables. I have converted categorical variables into one hot encoding. I have used Isolation forest algorithm to extract 5% of the ...
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144 views

Can I use categorical and numerical data variable at the same time in randomForest in r?

I have data in which few columns contain categorical data whereas remaining columns contain numerical data. I want to use random forest regressor from the randomForest library in r. So does this ...