Tagged Questions

The tag has no wiki summary.

learn more… | top users | synonyms

0
votes
0answers
9 views

Nuisance Variable in Random Forest Model

I know I have significant annual variation due to observer bias in my data and also unequal sample sizes between years. I wanted to account for this by using "year" as a nuisance variable in a random ...
2
votes
1answer
65 views

Random forest algorithm

I have a question about Random Forest algorithm: 1.Let the number of training cases be N, and the number of variables in the classifier be M. 2.We are told the ...
5
votes
1answer
124 views

Random forest and prediction

I am trying to understand how Random Forest works. I have a grasp about how trees are build but can not understand how Random Forest make predictions on out of bag sample. Could anyone give me a ...
0
votes
0answers
73 views

How does random forest, through the R package caret, make predictions?

I am using random forest (caret package in R) to predict unknown samples and classify them into one of eight groups. I am trying to determine how random forest places each sample into each group. I ...
0
votes
2answers
88 views

Classification in time series: SVMs, Neural Networks, Random Forests or non parametric models

My dataset is made of a label, $y_{t}$, which is the dependent variable, and about 20 columns of independent numeric variables, $X_{t}$, $t=1,2,...,T$. These samples are time series and my goal is to ...
1
vote
1answer
110 views

Random forest - binary classification vs. regression?

I have a dataset that I'm trying to classify into 2 groups, A and B, using a random forest model. I know the true grouping and I'm trying to see how well I can model it using the other available ...
0
votes
0answers
44 views

What is a good GINI decrease cutoff for feature inclusion based upon random forests?

I am using random forests to try and determine variable importance as part of feature selection for a model I'm working on, and while I can get ranked variable importance by mean decrease in GINI from ...
2
votes
0answers
72 views

Random forest with a mix of categorical and lexical features

I'm working on a binary classification problem for which the dataset is mostly composed of categorical features, but also a few lexical ones (i.e. article titles and abstracts). I'm experimenting with ...
1
vote
1answer
31 views

How to get the confidence interval around the variable importance generated by randomForest?

Using randomForest in R is it possible to get a variance or confidence interval around the importance of a variable (% difference in mean square error)? From the randomForest package ...
6
votes
1answer
93 views

Benchmark data for Random Forest evaluation

I would like to make/explore several alternative formulations of random forest (link) and am looking for the current state of the science for evaluating performance. In the reference file Leo ...
2
votes
1answer
140 views

Can we use random forest for classification in combination with distance matrix between classes?

With a colleague, we are working on a dataset containing ~5000 continuous variables for 120 individuals belonging to 8 classes. We want to estimate the relative importance of each variable to explain ...
14
votes
1answer
358 views

Random forest assumptions

I am kind of new to random forest so I am still struggling with some basic concepts. In linear regression, we assume independent observations, constant variance… What are the basic ...
1
vote
1answer
122 views

First steps learning to predict financial timeseries using machine learning

I am trying to get a grasp on how to use machine learning to predict financial timeseries 1 or more steps into the future. I have a financial timeseries with some descriptive data and I would like to ...
0
votes
0answers
40 views

Appropriate method for supervised learning of small data set with few variables

What method exc. for regression can be used in order to get y=f(x1,x2) on a training set of 800 to 2000 samples? y is a whole number <0,15>, x1,x2 are real <0,40>? I'm interested in prediction ...
2
votes
1answer
80 views

When to Log/Exp your Variables when performing Linear Regression?

I'm doing regression using Random Forests for predicting prices based on several attributes. Code is written in Python using Scikit-learn. How do you decide whether you should transform your ...
0
votes
0answers
57 views

What is the way to represent factor variables in scikit-learn while using Random Forests?

I am solving a classification problem using Random Forests. For that I have decided to use Python library scikit-learn. But I am new to both Random Forest algorithm and this tool. My data contains ...
0
votes
0answers
25 views

What are some references for works which used synthetic True Negatives for the purpose of training a classifier?

I am searching for previous research papers which used a synthetic True Negative set for training a classifier (preferably a Random Forests one). The synthetic true negative set could have been built ...
1
vote
0answers
47 views

Which Regression methods are suitable for binary valued features and continuous output?

I want to build a machine learning model to regression on continuous output given binary valued features(0,1). the dimension of my problem is around 200. which of the flowing methods seems suitable ...
1
vote
4answers
145 views

Measuring representativeness of a sample using covariates

I was provided with quite a small sample of labeled (variable of interest) observations to train a model to predict unlabeled observations. All the observations are associated with many covariates. ...
0
votes
1answer
51 views

Loss Matrix Equivalent with Neural Networks and random Forest

I'm doing classification (0,1) on a dataset for which different types of errors should be weighted differently. IE, false positives would be weighted 10 x more than false negatives. In decision ...
3
votes
1answer
69 views

Random Forests and data transformations

I've started reading about Random Forests and one of the attributes that appeals to me is that they are good at dealing with independent variables that interact with one another. Does Random Forest ...
2
votes
1answer
65 views

Do the predictions of a Random Forest model have a prediction interval?

If I run a randomForest model, I can then make predictions based on the model. Is there a way to get a prediction interval of each of the predictions such that I ...
2
votes
0answers
39 views

Maximum number of classes for RandomForest multiclass estimation

I have researched the internet|literature a lot on multiclass prediction to find out what is a realistic limit for the number of classes that can successfully be used for estimation when using a ...
0
votes
2answers
57 views

Positive, Likely Positives and Unknowns in Random Forests

It is my first question here, so my excuses if my contribution is naïve. I'm facing a classification problem in which I have a minority class (~100 samples) labeled as "Positive", another class ...
2
votes
0answers
61 views

Using probability scores from a random forest

I've the following problem. I've a data set that tries to predict whether a given buy event will happen or not (0/1) when a customer sees a certain product, and I've features created for both the ...
0
votes
1answer
39 views

Relative importance weight with cforest

I am new in using RF. I want to use it to compute the relative importance of the features. I found the weight is very small ("party" package, cforest). Is there anyway to get these weights in a range ...
4
votes
1answer
174 views

How to associate the probability output of a Random Forest classifier with reality

I am currently working with the national forest inventory of Mexico. A sample sceheme that collected data concerning the state of forests on points spread out all over the country. One of these ...
0
votes
0answers
32 views

Various models not improving basic rpart result

I have a data set with 10,000 or so samples in it and 100 or so features. I've created a training set and test set and am trying to predict a numeric value. I've used rpart to determine the most ...
0
votes
0answers
47 views

Weighting and time series with machine learning

I'm trying to produce a model to predict the price of a product on the basis of several factors effecting previous time-stamped sales. I am certain that older sales are less relevant to the prediction ...
11
votes
2answers
267 views

Practical questions on tuning Random Forests

My questions are about Random Forests. The concept of this beautiful classifier is clear to me, but still there are a lot of practical usage questions. Unfortunately, I failed to find any practical ...
3
votes
1answer
76 views

Variable importance randomForest negative values

I am asking myself if it is a good idea to remove those variables with a negative variable importance value ("%IncMSE") in a regression context. And if it gives me a better prediction? What do you ...
2
votes
1answer
67 views

probability distribution of output value with regression tree methods

If I have a regression problem where I try to estimate the value of $y$ as function of $x_1 \dots x_d$: $$ y = f(x_1,\dots,x_d) $$ using a Boosted Regression Tree or a Random Forest Regression, is it ...
2
votes
2answers
190 views

Random forests vs boosting

I thought it would be interesting to talk about two of the best ensemble methods off-the-shelf: Random Forests and Boosting. When would you apply one method rather than the other one?
2
votes
0answers
117 views

Using LASSO on random forest

I would like to create a random forest using the following process: Build a tree on a random samples of the data and features using information gain to determine splits Terminate a leaf node if it ...
3
votes
1answer
113 views

Battery of random forest models for each class

I have a dataset which consists of roughly 40,000 observations grouped into 12 classes. I did a quick random forest run on a single split of 80% training and 20% testing (Dont bring up the discussion ...
1
vote
1answer
62 views

Non-independence of IVs in a random forest model

How is a random forest model affected if some of the variables are not independent?
2
votes
0answers
78 views

Random Forest or other machine learning techniques with paired samples

I am trying to select features from paired samples and was wondering if there are methods out there that adapt random Forest or other machine learning algorithms to paired samples i.e. if randomForest ...
3
votes
1answer
332 views

Multiple curves when plotting a random forest

I performed a random forest using the randomForest package. I know that if I plot the random forest using the plot() command, I ...
1
vote
1answer
119 views

RandomForest factor with too many levels

I have a model with about 200,000 training observations, where I am regressing, with 4 factors and 2 continuous variables. One of my features has 927 levels, which is causing the R implementation of ...
1
vote
1answer
225 views

Converting R's Random Forest model to Mahout

I need to implement an RF created by R on Hadoop. I know a way is to recreate the random forest with the same training data using Mahout. But is it possible to convert the RF created by R directly ...
2
votes
1answer
123 views

Building the dataset for Random Forest training procedure

I should use the bagging (bootstrap aggregating) technique in order to train a random forest classifier. I read here the description of this learning technique, but I have not figured out how I ...
4
votes
0answers
130 views

Predicting count data with random forest

Can a Random Forest be trained to appropriately predict count data? How would this proceed? I have quite a extensive range of values so classification doesn't really make sense. If I would use ...
0
votes
0answers
86 views

Missing measure of variable importance for randomForest package in R [closed]

I have a problem with the importance measures given by the randomForest package in R. I pass the parameter importance=TRUE to my ...
2
votes
0answers
69 views

how to calculate partial dependence when I have 4 predictors?

I was reading Freidman's book "The elements of statistical learning-2nd edition". Page 365, it talks about partial dependence plot. I don't quite understand how he actually calculates partial depence ...
0
votes
1answer
118 views

It is possible to implement a regression algorithm using Random Forests?

I have to write code to implement regression using random forests (by default Weka provides random forests for classification). Is this possible to do?
2
votes
1answer
194 views

Caret and randomForest number of trees

I am puzzled as to why the caret package in R does not allow tuning on the number of trees (ntree) in a random forest (specifically in the randomForest package)? I cant imagine this is an oversight on ...
1
vote
1answer
58 views

Selection of “best split” at a given node in RF

At a given node, random forests sample k (aka mtry) variables (predictors). Then they pick the variable for which they get the ...
2
votes
1answer
264 views

How do I calculate prediction intervals for random forest predictions?

In regression problems random forests yield a prediction for each case by averaging the results of each single tree in the forest. I would like to draw a 95% prediction interval around each ...
0
votes
0answers
114 views

How do BART (Bayesian Additive Regression Trees) work?

I am confused about two concepts about the BART model: How is each tree created? i.e. is a random sample taken from the training data and the tree built from that sample (as in random forests), or ...
3
votes
1answer
289 views

Imputation with Random Forests

I have two questions on using random forest (specifically randomForest in R) for missing value imputation (in the predictor space). 1) How does the imputation algorithm work - specifically how and ...

1 2 3 4