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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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Error in randomForest.default(m, y, …) : Can't have empty classes in y

I am quite new to R and I am having some difficulties with a random forest I am trying to implement. my Y (Nationality) is a factor that should have 2 values "Japan" and "Mexico" but when I try to ...
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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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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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28 views

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
26 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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8 views

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
30 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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18 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
23 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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15 views

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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17 views

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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548 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
18 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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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
25 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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17 views

Huge difference in accuracy when using two datasets (instead of one) for text classification in Python

Recently I started reading more about NLP in order to learn more about the subject. The problem that I've encountered, now that I'm trying to make my own classification algorithm (the text sends a ...
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1answer
34 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
11 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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63 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
82 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
21 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
15 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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75 views

Random Forest with cross validation using TreeBagger on Matlab

I'd like to do cross validation on a Random Forest model. I've tried using crossval but it doesn't work on TreeBagger. I tried using for loop, but I'm not sure it's correct: ...
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27 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
36 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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Training on continuous data for profile regression

I have a large data set consisting of millions of 1-dimensional profiles. The profiles themselves are arbitrarily complicated continuous functions, $f(x)$, each bound from $0 < x < 1$. These ...
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1answer
44 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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2answers
139 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
22 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
61 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
50 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
51 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
193 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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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
23 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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1answer
66 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 ...
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1answer
18 views

Working with few instances of specific target feature over large dataset

I have data over a single, a machine includes different components, all the parts are interacting, the data are tracked for those parts, it tracks power consumption and many other relevant feature ...
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24 views

randomForest in R - skip test

I am working with package randomForestin R for predicting a price in an hourly basis. For creating the model, after partitioning the dataframe, I use the following ...
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40 views

“Histogram and binning” technique for categorical variables publication and implementations

H2O.ai have implemented the "histogram and binning" technique for efficient and accurate tree-building using categorical variables of high cardinality (>100): http://docs.h2o.ai/h2o/latest-stable/h2o-...
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1answer
24 views

Post training classifier configuration

I have a behaviours vector representing some identity. I need to binary classify [malicious or benign] each instance [ideally with a normalised severity score]. For that I can use a variety of linear ...
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2answers
58 views

I need to force my random forest model to learn one crucial relationship between features. How can I achieve that?

Say, given 10 independent features as input to my RF model, when feature 1 and feature 3 are 100 (or less), my model output must be 5 despite the values of the other features. How can I teach that ...
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create random forest using decision trees generated by different decision tree algorithms

We're planning to conduct a data mining study which will be using ID3, C4.5 and CART algorithms. Naturally, this would then generate three different decision trees. Would it be possible to create a ...
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1answer
83 views

Using GridSearchCV and a Random Forest Regressor with the same parameters gives different results

As the huge title says I'm trying to use GridSearchCV to find the best parameters for a Random Forest Regressor and I'm measuring my results with mse. ...
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Predicting relative performance of algorithm configurations on a task

Setup I have a set of tasks $T = t_0, \dots, t_k$, and an algorithm that can be configured with a set of settings $S = s_0, \dots, s_m$. Each task $t_i$ also has a set of properties $P_i = p_0, \dots,...
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2answers
38 views

How to visualize Ensemble Models ( Random Forest) with 1000 estimators

I am working on classification problem where I need to categorize the user in buy/ non-buy category. I have around 100 + features or predictors to predict the behavior of user. I tried to implement ...
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30 views

“Binary Encoding” in “Decision Tree” / “Random Forest” Algorithms

Is it OK to use Binary Encoding in a dataset containing categorical columns with very high cardinalities? Some facts about my dataset: My dataset has ~170000 rows One of the categoric variables has ...
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0answers
30 views

Is this random forest logical correct and correct implemented with R and gbm?

For professional reasons I want to learn and understand random forests. I feel unsafe if my understanding is the correct or if I am doing logical errors. I got a data set with 15 million entries and ...
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1answer
40 views

Running multiple random forest and combining them

I am trying to build a random forest model in R (RStudio). My training dataset has around 2 million rows and 38 variables. When I tested 5000 rows from this dataset I was able to build the random ...
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2answers
132 views

Error in using fit() on RandomForest Classifier where X was a pandas.DataFRame object

On using fit() method on sklearn.ensemble.RandomForestClassifier I am getting a value error that says. ValueError: could not convert string to float: 'male' The ...
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1answer
417 views

Xgboost performs significantly worse than Random Forest

I have a dataset of 3500 observations x 70 features which is my training set and I also have a dataset of 600 observations x 70 features which is the test set. The target is to classify observations ...