0
votes
0answers
7 views

FNN package for R - possible to use manhattan or other distance metrics? [on hold]

It is possible to change the algorithm, but I am stuck trying to change the distance metric. I know it usually makes little difference, but in this case I need it!
5
votes
0answers
61 views
+50

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
14 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
17 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
13 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
66 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
20 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
177 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
8 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
35 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
41 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= ...
-2
votes
0answers
22 views

analyzing neturalnet function from R [duplicate]

'neuralnet' package in R allows us to use neural network algorithm with back propagation. I want to use the function for prediction. I saw a tutorial on neuralnet in which iris data was predicted. I ...
0
votes
0answers
58 views

Decision tree in R

I am new to machine learning in R. This is my data set. ...
1
vote
1answer
36 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
42 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
32 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
26 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
79 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
28 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
59 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
27 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
57 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
44 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
47 views
0
votes
0answers
30 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
46 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
59 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
110 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
78 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
105 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
119 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
161 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
33 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
28 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
51 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
29 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) ...
2
votes
0answers
139 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
62 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
43 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 ...
0
votes
2answers
67 views

Determine if difference in class distribution is statistically significant

I have a dataset of some observations with class attribute of values 0 and 1. The dataset is quite unbalanced (class 1 – 15%, class 0 – 85%). Further this dataset consists of 5 years, and the ...
0
votes
0answers
46 views

Data Mining study and prediction of a Dataframe in R

I'm new in the Data Mining World. I have a Dataset of 19 variables(some of them categorical). It is about execution time of different aplicattions. I have something like this) but with thousands of ...
0
votes
0answers
41 views

Hidden Markov Models methods for selecting optimal number of states

Package RHmm (R) I have a vector which I fit into a hmm model in an attempt to select an optimal number of states for a hidden markov model. ...
3
votes
2answers
263 views

How to do multivariate machine learning? (predicting multiple dependent variables)

I am looking to predict groups of items that someone will purchase... i.e., I have multiple, colinear dependent variables. Rather than building 7 or so independent models to predict the probability ...
0
votes
1answer
26 views

Some Basic things we need to do when we are doing text classification

I am working on a project where I have to do multi-label text classification. I want to understand that whether my approach is correct or I am missing something. I am using R to do it. Clean ...
2
votes
3answers
100 views

Dealing with different time series data in Machine Learning

I am trying to create a stock market model based on fundamental variables for the US economy. I am using R. Some of the variables I am looking to include are: GDP, Unemployment Rate, Initial Claims, ...
2
votes
1answer
132 views

How to implement a hold-out validation in R

Let's say I'm using the Sonar data and I'd like to make a hold-out validation in R. I partitioned the data using the createFolds ...
2
votes
1answer
190 views

Relative importance of a set of predictors in a random forests classification in R

I'd like to determine the relative importance of sets of variables toward a randomForest classification model in R. The ...
2
votes
1answer
89 views

Imbalanced training dataset and Random Forest regression model

I have a large dataset (>300,000 observations) that represent the distance (RMSD) between proteins. I'm building a regression model (Random Forest) that is supposed to predict the distance between any ...
2
votes
2answers
111 views

Area under the ROC curve or area under the PR curve for imbalanced data?

I have some doubts about which performance measure to use, area under the ROC curve (TPR as a function of FPR) or area under the precision-recall curve (precision as a function of recall). My data is ...