0
votes
0answers
7 views

strucchange problem with csv files

I'm new to R and I am interested in strucchange package. I have two codes; code1 and code2. ...
1
vote
0answers
24 views

Has anyone publicly shared an implementation of RUSBoost in R?

There's no package available on CRAN, so I was hoping someone in the community had written their own function/package. I see it's been done in MATLAB, so I may just have to start with that and write ...
0
votes
0answers
12 views

How to handle large .csv file in R? [migrated]

I have a large(>100,000) single column floating point time-series data. I want to find structural changes within the data with respect to time( in my case index). In-order to do that, I am using R ...
-1
votes
0answers
40 views

Sales Forecasting using Support Vector Machine

I have sales data for last three years 2011-2013. I want to use Support Vector Machine technique in R to do the predictions. I just wanted to know that the approach that I am using is correct or not? ...
0
votes
1answer
29 views

Multi-class Confusion Matrix to Binary confusion matrix

i know the main concepts of data/text mining but i used them mainly in binary classification problems (just two classes). i am now dealing with a problem with 8 classes and i am atruggling how to ...
0
votes
1answer
54 views

How to determine which variable or combination of the variables are affecting to the predictor variable?

I have one dependent variable name as "win ration" of the deal contested and more than 30 independent variables, all are categorical variable name as role of the customer, geo, region, and 27 ...
2
votes
2answers
91 views

Reproduce linear discriminant analysis projection plot

I'm struggling with projection points in linear discriminant analysis (LDA). Many books on multivariate statistical methods illustrate the idea of the LDA with the figure below. The problem ...
0
votes
0answers
29 views

Obtaining sequence of lambda values for training glmnet model via `caret`

I have multiple models that I'm training using train in the caret package, all while using the same cross validation folds to ...
1
vote
0answers
19 views

How to give an input when you are using Machine Learning method in R

I am new to R and machine learning algorithms. I have basic knowledge of different machine learning algorithms. I have four years of daily sales data.I am trying to predict sales using Support Vector ...
2
votes
1answer
43 views

Differences in AUC calculation between pROC and ROCR

Does anyone know the difference in calculation between these two AUC packages? They get different results when I add in positives with predicted value of 0 (simulating a prob model where many outputs ...
6
votes
2answers
150 views

Clustering a noisy data or with outliers

I have a noisy data of two variables like this. ...
0
votes
1answer
33 views

kernels and similarity (in R)

I am trying fit different kernels to calculate similarity matrix in R. Here is example data - X matrix : ...
11
votes
2answers
143 views

Bayesian lasso vs ordinary lasso

Different implementation software are available for lasso. I know a lot discussed about bayesian approach vs frequentist approach in different forums. My question is very specific to lasso - What are ...
0
votes
0answers
16 views

A framework for comparing the performance of Expectation Maximization

I have my own implementation of the Expectation Maximization (EM) algorithm based on the following paper http://pdf.aminer.org/000/221/588/fuzzy_k_means_clustering_with_crisp_regions.pdf I would like ...
0
votes
0answers
24 views

Method to select meaningful features for nearest neighbor classification

i try to perform some k nearest neighbor classification in R. That for i want to select the most meaningful features to deal with the curse of dimensionality. I have already decided to use Mahalanobis ...
0
votes
0answers
18 views

After applying SVD, how do I find which features from my original dataset were most significant?

I'm using MathNet.Numerics library in C# to find the SVD but the Sigma matrix gives no indication of which values correspond to which features. It simply lists them in the most significant order. ...
1
vote
1answer
89 views

Analysis of Customer satisfaction surveys

I have customer feedback data about 2-3 products from 100 customers. Number of questions are around 160. I have data in excel format. Header row contains the question and row below contains the ...
0
votes
0answers
24 views

Predict feature combination with highest probability

I trained a Support Vector Machine with the caret package in R. My dataset looks the following: ...
1
vote
2answers
237 views

Estimate ARMA coefficients through ACF and PACF inspection

I know that this is probably a question that's been asked plenty of times, but i haven't seen an answer that's both accurate and simple. How do you estimate the appropriate forecast model for a time ...
1
vote
0answers
12 views

determing states in HMM with BIC

I'm fitting a HMM to time series, for each data set I use BIC results to select the optimum number of states. In that, the BIC number is lowest and thereby indicating this model with that number of ...
0
votes
1answer
56 views

Way to train Hidden Markov Model in R with multiple sequences

i have multiple sequences for each of two states. I'd like to train a HMM with these to predict the state for unkown sequences. Here is an example for this problem: ...
2
votes
0answers
45 views

Predicting the Success of a tweet

I want to predict the success of a tweet. In my case a tweet is successful when the sum of the number of favorites and the number of retweets is greater than 5. So my outcome value y is: y= ...
0
votes
0answers
65 views

Decision tree in R

I am new to machine learning in R. This is my data set. ...
1
vote
1answer
44 views

What does the parameter $\alpha$ do in the Jaccard method for binaryRatingsMatrix in R recommenderlab?

What is the role of the parameter 'alpha' in the recommenderlab R package's use of Jaccard method in the recommender model for ...
0
votes
2answers
63 views

Best feature selection method for naive Bayes classification

i want to make classification with naive Bayes. I have got about 100 Features. Numerical ones as well as categorical ones. Since i want only the most relevant ones to be included for the ...
0
votes
1answer
46 views

Question about normalize/scale data before using neuralnet

I have read several threads about the issue on same outputs after people fitting a neural network model with R neuralnet. Posted Solution is to normalize or scale the data before fitting model. Since ...
0
votes
0answers
50 views

Combining CostSensitiveClassifer with MultiClassClassifier [RWeka]

this is my first attempt at posting here. I looked through CrossValidated and found two similar problems without answers (see How to combine WEKA classifiers and Combine MultiClassClassifier and ...
0
votes
1answer
90 views

Machine-Learning algorithms for Forecasting

For work, I'm working on an app where you essentially forecast the failure rate of the overall machine through different factors such as the historical failure rates for the components used to build ...
1
vote
0answers
45 views

Random Forest regression model in R and data overfitting

I have trained my random forest model on a 74,000 training examples where each example consists of two proteins Amino Acids sequence (20 characters) and some numeric values representing the similarity ...
3
votes
0answers
79 views

Generalized linear model with lasso regularization for continuous non-negative response

I have a big data problem with a large number of predictors and a non-negative response (time until inspection). For a full model I would use a glm with Gamma distributed response (link="log"). ...
1
vote
0answers
47 views

Online model training in R, without a static data

Let's say I have a model in R, a regression tree created by "glm",using "data1" dataframe: Model1 = glm(DepVar ~ . ,data=data1,family="binomial") Is there a way ...
0
votes
0answers
43 views

How to handle the error of glmnet package for non-positive lambda?

I'm using glmnet package to learn regression models,it works fine, but for some models, I face an error and my script stops running. Here is my effort: ...
2
votes
1answer
93 views

Is there a decision-tree-like algorithm for unsupervised clustering?

I have a dataset consists of 5 features : A, B, C, D, E. They are all numeric values. Instead of doing a density-based clustering, what I want to do is to cluster the data in a decision-tree-like ...
0
votes
1answer
47 views

Machine Learning on Percent/Continous Dependent Variable

I have a large dataset of 30,000 cases with 150 variables. I am looking for a few possible machine learning solutions/methods that I could try and use for cross validation. My dependent variable ...
1
vote
0answers
57 views
0
votes
0answers
35 views

Build corpus with phrases

I have my documents as: doc1 = beautifull, very good, very bad, you are great doc2 = very bad, good restaurent, nice place to visit I want to make my corpus ...
3
votes
1answer
55 views

Difference in tf-idf values in R

I am playing around in R to find the tf-idf values. I have a set of documents like: ...
1
vote
1answer
85 views

Create a matrix of tf-idf values from documents

I have a set of documents like: D1 = "The sky is blue." D2 = "The sun is bright." D3 = "The sun in the sky is bright." and a ...
2
votes
1answer
157 views

Regression Trees / Boosted Regression Trees for Tweedie Distribution in R

I am currently working at work on a project that attempts to predict an environmental change variable. I am personally not a huge fan of the project, but I still want to do the best job possible. ...
0
votes
3answers
98 views

Implementing R Machine Learning Model in Real World

I've been able to create some successful R ML models using some of the popular machine learning algorithms. However, I'm not sure how to implement the model where the end users (technically ...
2
votes
2answers
118 views

random forest for large number of variables and predictions

I have very large number of variables compared to samples they are measured on. The following is example data in R. ...
0
votes
1answer
157 views

Train / Validate / Test sets in Caret

I want to use caret to compare two different classification algorithms. For example SVM and Elastic net. I want to put aside some samples for test set and then use the rest of the samples for ...
1
vote
2answers
180 views

Machine Learning and R textbook reference

I am asking for a book reference to further my studies in machine learning with the R programming language. Feel free to reference multiple books that are just machine learning or just R programming. ...
1
vote
0answers
35 views

Hierarchiqual prediction using R

I'm pretty new in R, and I couldn't find any information about a package who can do the following: supposing that I have a set of data (for instance, different text documents), which can have several ...
0
votes
0answers
29 views

Is there a neural network r package for mixed model?

R neural network package such as nnet does not allow to specify random variables. I have a dataset with repeated measures of the same subject, which introduce random effects as in a general linear ...
1
vote
0answers
66 views

How can I improve the accuracy of my logistic regression code, which tests the accuracy using the 10-fold cross-validation technique?

How can I improve the accuracy of my logistic regression code, which tests the accuracy using the 10-fold cross-validation technique? I have implemented this code using ...
0
votes
0answers
34 views

I need an insight on result of my analysis

I need some help/insights on result of my data analysis. My object is to classify 3 types of different numbers. ie) 1 or 2 or 3 I built C5.0 tree + leave group out cross validation (hold out) ...
3
votes
1answer
224 views

Prediction of continuous variable using “bnlearn” package in R

I use bnlearn package in R to learn the structure of my Bayesian Network and its parameters. What I want to do is to "predict" the value of a node given the value of other nodes as evidence ...
1
vote
1answer
65 views

What are the most effective R packages for classification problems? [closed]

Let's say we have data of the following form: a categorical response $y$ and covariates $x_1,x_2,...,x_p$ that can be either categorical or continuous (a very common scenario). Further, let's say the ...
1
vote
0answers
46 views

Random Forest and Factor Predictors [duplicate]

How do decision tree based ensembles like random forest deal with categorical ("factor") predictor variables? My guess would be that indicator variables are created for each factor via a ...