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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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NLP features for Random Forest model

I want to train a Random Forest model with some NLP features together with some other categorical and numerical features. Hence, I have create a dictionary and I am wonder who to deal with such ...
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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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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
42 views

Using deep learning or random forest [on hold]

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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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
16 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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35 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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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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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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14 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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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
26 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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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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“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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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
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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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56 views

Best approach to predict best time to call for call center log data?

Doing all the below things in R, I have a call logs data of a call center. variables are "date_time" , "callerID" , "Phone_number" , "call_duration". date_time is of POSIXct type , i have extracted ...
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2answers
50 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
194 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 ...
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28 views

Do I choose regression tree split point randomly?

I am interested in using random forest for regression purpose and I understand that random forest is an ensemble of regression trees. What makes random forest different is instead of finding the best ...
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5 views

Are the data points taken in a Random Forest Regression for each Tree of same size?

In Random Forest Regressors we know that each decision tree takes k data points which is less than the total data points n and train the model. My question is is this k arbitrary? Or there's a ...
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2answers
23 views

Misclassification Rate for Random Forest Plateauing too Early

Using R, I have created 5 different random forest models using 5 different numbers of trees (3,10,30,100,300). My intention was to compute the misclassification rates of each of these models and plot ...
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Predicting both - classification and regression with time series random forest

so I'm developing a sports book betting system. So my goal is to choose appropriate ML approach to predict client's next bet based on the history of other clients' bets. Its regression and ...
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1answer
197 views

overfit a Random Forest

I am trying to overfit to the maximum a random forest classifier using scikit-learn to make some tests. Does somebody know what hyperparameters I can tune to do that? Or does somebody know which ...
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1answer
28 views

Feature importance ratio

I trained a Random Forest classifier (sklearn) and consequently computed the feature importance and consequently ranked them. The forest has 100 estimators. My top 5 features with their importances ...
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1answer
29 views

How we can have RF-QLearning or SVR-QLearning (Combine these algorithm with a Q-Learning )

How we can have RF-QLearning or SVR-QLearning (Combine these algorithm with a Q-Learning )? I want to replace the DNN section of Qlearning with a RF or SVR but the problem is that there is no clear ...
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1answer
25 views

Is the neural network in DQN used to learn like a supervised model?

Is the neural network in DQN used to learn like a supervised model?
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18 views

Error while accessing prediction results on Zeppelin

I trained a RandomForestClassifier(rfModel) on Zeppelin and trying to test it using raw data. I am running into error when I try to access the predicted dataframe using show()/print functions. Any ...
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1answer
44 views

Why does Bagging or Boosting algorithm give better accuracy than basic Algorithms in small datasets?

I was working with a small dataset, with 392 values, and it was kind of an imbalanced dataset, with 262 values belonging to class 1 and rest 130 to class 0. So I did the upsampling technique, ...
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1answer
276 views

'RandomForestClassifier' object has no attribute 'oob_score_ in python

I am getting: AttributeError: 'RandomForestClassifier' object has no attribute 'oob_score_'. But I can see the attribute ...
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1answer
38 views

Scikitlearn grid search random forest using oob as metric?

Have looked at data on oob but would like to use it as a metric in a grid search on a Random Forest classifier (multiclass) but doesn't seem to be a recognised scorer for the scoring parameter . I do ...
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2answers
24 views

Support Vector classifier perform well with input features rather than transformed features in contrast to ANN-BP, random forest (other classifiers)

I am working on stock data with 5 raw features (OHLCV). Using few transformations used by technical analysts, have created 20 more features giving different kinds of indications. When trying to ...
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20 views

Random Forest for Edge Detection

Background: This project, Fast Edge Detection Using Structured Forests (written in MATLAB and C++), developed by Microsoft Research, applies random forest to detect edges from an image. The ...
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1answer
510 views

How to implement feature selection for categorical variables (especially with many categories)?

I've been trying to get some ideas of how I could treat categorical variables when doing feature selection. Mainly I've been running Random Forest feature importance on Python for which preprocessing ...
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2answers
35 views

Evaluating clusters (e.g. built by kmean) using Random Forest

I have made clusters for my data set (1.5 million samples and 800 features) using k-mean. I am aware of internal indices for evaluating clusters. However, I was thinking about training a supervised ...
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1answer
15 views

Preventing fitting Regression CNN to the mean when dataset has only few outliers

I am trying to train a CNN for regression on a dataset where most of the points lie around a similar output value. There are however a few outliers that are very important but they are less ...
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Practical Questions on Isolation Forests

Note: This may also apply to random forests I don’t know, please modify title and question if necessary. I have a few short questions, any answers would be great: From my understanding, the forest ...
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1answer
53 views

Poor Precision-Recall curve for binary classifier trained on balanced data, with imbalanced test data

I have an very imbalanced dataset (9:1), for which I have performed under-sampling and achieved a balanced training set (~130k samples total post balancing). I am performing classification using ...
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1answer
34 views

Evaluating the performance of a random forest classifier

I'm using a random forest classifier (in R) to impute missing data in a dataset. Basically, I have a bunch of objects (companies) and I want to guess an attribute (...
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1answer
32 views

Is random forest better suited than neural network in my scenario?

I am learning Neural network and facing this scenario. Say in my input, X has 20-30 features, and Y is a classification (e.g. 1,2,3,4, 5). What I need is to find the features that contribute most to ...
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2answers
130 views

How to select features for Text classification problem

I am working on a problem where we need to classify user query into multiple classes. Problem: Suppose we are running a website for selling products. The ...
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6answers
634 views

I got 100% accuracy on my test set,is there something wrong?

I got 100% accuracy on my test set when trained using decision tree algorithm.but only got 85% accuracy on random forest Is there something wrong with my model or is decision tree best suited for the ...
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1answer
24 views

Ensemble models - neural network input both original data and predictions of other models?

From my understanding in order to improve accuracy with ensemble models you need a wide range of independent ensemble methods. I was wondering whether using the ouput of a random forest model as one ...
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1answer
114 views

Interpretation of variable or feature importance in Random Forest

I'm currently using Random Forest to train some models and interpret the obtained results. One of the features I want to analyze further, is variable importance. The thing is I am not familiar on how ...
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2answers
73 views

Why is this Random Forest perfect?

I'm learning Random Forest Classifier from a video, where the instructor got a score of 0.44, while I'm getting 0.9985 ( But actually it's perfect). Did I overfit it? If so what is the next step? ...
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1answer
32 views

Can I create random forest with RandomForestClassifier which will consist the same trees?

Based on answers to this question I should be able to build random forest with all the same trees by using bootstrap = False, max_features = None, random_state = 42 parameters. I wrote quick code to ...