0
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0answers
25 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
141 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
20 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 ...
1
vote
2answers
46 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, ...
1
vote
1answer
34 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
85 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
50 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 ...
1
vote
2answers
55 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 ...
1
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0answers
42 views

Exploratory Analysis - finding the most important factor

I have a dataset of 113 variables. In exploratory analysis the first thing I want to know is what are the most important factors on a single variable (revenue). I learned that naive Bayes would ...
0
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2answers
46 views

Machine Learning with Skewed Classes in R

I am looking for some suggestions on what methods are appropriate for training a dataset with a high skew in the outcome classes. The ratio of Class 0: Class 1 is about 20:1 and I am looking to ...
0
votes
0answers
30 views

Which diffusion of latent Dirichlet allocation is helpful for assign the words corresponds to each topic?

In my corpus documents I have two different subjects. Which diffusion of LDA (asymmetric or symmetric) could help for assigning the words corresponds to Subject 1 and Subject 2 in my Topics? Here is ...
1
vote
1answer
46 views

Divergence measure of two classifiers' performance?

I have two classifiers built with the same data. How can I measure divergence of these models? I found something like DIC but I don't know how to calculate this in R?
0
votes
0answers
53 views

Association Rules in R

I have a Dataset - with columns like Transaction No , Store No ,Division, ...
0
votes
2answers
100 views

step by step tutorial for newbie

I'm looking to join the field of statistics and more exactly to forecasting. I'm a software developer and I just started playing with R. Can you recommend me some tutorials related to forecasting, ...
0
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0answers
42 views

Gather insights from quarterly financial forecast data

I am trying to analyze a quite large (~25,000 rows) dataset of financial forecasts. The forecasts are usually not derived from algorithms, but come from a large number of analysts who forecast the ...
2
votes
0answers
30 views

Identifying what weights to give to each class in a Random Forest

I am using a randomForest package in R to discriminate between 4 categories. My data consists of 80+ observations and is heavily unbalanced with around 70% of all observations being in a single ...
0
votes
0answers
102 views

Which prediction algorithm fitted for prediction in R

I was used R and mongodb for finding predictions of next date outcome for that I write R code as below ...
3
votes
1answer
163 views

Understanding the output of C5.0 classification model using the CARET package

The C5.0 classification model was used in this 4-class problem data with $N_{train}$=165, $P$=11, using caret R-package by ...
1
vote
2answers
78 views

Weighting more recent data in Random Forest model

I'm training a classification model with Random Forest to discriminate between 6 categories. My transactional data has approximately 60k+ observations and 35 variables. Here's an example of how it ...
1
vote
1answer
118 views

What machine learning technique I need to apply?

I have a unix shell data. Each session starts with <begin> and <end>. Between ...
2
votes
1answer
63 views

Comparison of CPH, accelerated failure time model or neural networks for survival analysis

I am new to survival analysis and I've recently learned that there are different ways to do it given a certain goal. I am interested in actual implementation and appropriateness of these methods. I ...
0
votes
1answer
42 views

Shrinkage parameter in Adaboost?

I'm unclear how the shrinkage parameter works in Adaboost. I understand the concept of shrinkage in the theoretical sense related to ordinary least squares, but I'm not sure how to interpret this ...
3
votes
1answer
301 views

R neural network model with target vector as output containing survival predictions

Overview I want to simulate the survival prediction using neural networks described in this paper entitled "Application of Artificial Neural Network-Based Survival Analysis on Two Breast Cancer ...
5
votes
0answers
72 views

Compressed sensing: Optimization in $L_1$ norm and total variation with fourier coefficients

I'm reading the article Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete Frequency Information (Candes, Romberg and Tao, 2004). In this article they are talking ...
3
votes
1answer
207 views

Can Random Forests do much better than the 2.8% test error on MNIST?

I haven't found any literature on the application of Random Forests to MNIST, CIFAR, STL-10, etc. so I thought I'd try them with the permutation-invariant MNIST myself. In R, I tried: ...
1
vote
1answer
187 views

Neural network for prediction

I am working on neural networks for a regression problem in R using packages like nnet, caret etc. I have split my data into ...
1
vote
0answers
138 views

Predicting Naive Bayes model in R on a test data with a single record

I built a naivebayes model using the Housevotes84 data(discrete data) in mlbench package- model <- naiveBayes(Class~., data=HouseVotes84) I took one record ...
1
vote
1answer
63 views

Plot cost function for Random Forest against sample size in R

I would like to aestimate the cost function of a random forest model fed by several subsets of my training/test data. The subsets are increasing in size. Comparing the cost against the training and ...
0
votes
1answer
116 views

Step-wise feature selection with caret

can anyone direct me to a package/commands in R for performing step-wise feature selection, preferably using the caret package. I have already used linear ...
1
vote
1answer
233 views

Does party package in R provide out-of-bag estimates of error for Random Forest models?

I'm a new R user, and also new to Random Forest modeling. I cannot seem to figure out how to obtain the out-of-bag (OOB) error estimates for cforest models built with the Party Package in R. In the ...
1
vote
0answers
115 views

Significance of R Squared in Random Forest / GBM and GBM Tuning Parameters

I often get different level of responses when I discuss about R-Squared and its relevance to measuring the performance of a Random Forest or GBM model. In general, RMSE is a better and more ...
4
votes
1answer
135 views

2D binary classification

Background A laboratory wants to evaluate whether a certain form of gel electrophoresis is suited as a classification method for the quality of a certain substance. Several gels were loaded, each ...
0
votes
0answers
45 views

Loss function of kernlab

I'm looking for the default loss function the ksvm()-function from R package 'kernlab' is using. My guess is the Hinge Loss but I cant find any reference or citation for it (There's nothing ...
1
vote
0answers
85 views

Organizing data to feed random forests

I'm willing to apply machine learning with R (I will start with random forests then maybe have a look at NNs) on some data, but I don't know where to start, ...
1
vote
1answer
238 views

Prediction using Naive Bayes of klaR package fails

I am trying to replicate a example that I found in Tom Mitchell's book Machine Learning (1997), using R. It is a example from chapter 6. There are 14 training examples (shown below) of the target ...
1
vote
1answer
134 views

Time Series Modeling with Lagged Variables

I have a dataset with columns that represent lagged values of predictors. To illustrate with a simple example, suppose we had car sales data for 3 years and the only predictors available were income ...
0
votes
1answer
125 views

Gradient boosting in R uses only a single variable

I am trying to build a boosting model using the package gbm in R. I have the following code: ...
3
votes
1answer
128 views

Use hierarchical clustering in R to cluster items into fixed size clusters

I am trying to use R to do Kmeans clustering and as most people I ran into the challenge of determining when to finish. I have 10,000 items and potentially 10 times of that down the road. My goal is ...
0
votes
0answers
30 views

Minimizing Specificity in Adaboost (and other) Classifiers

This is a relatively simple question, but is not addressed in the documentation for the ada package in R. How do I go about instructing ...
0
votes
0answers
99 views

SVM prediction accuracy drops when using Test data

I am using the Kaggle Scikit data to learn R. I am using the R e1071 SVM function to predict classes. When I use: ...
1
vote
1answer
89 views

How bagging on CART (RPART) is different from CART with cross validation?

I am wondering is there any difference between the following two algorithms: RPART (Recursive partitioning) in R, with cross-validation (xval = 10, default) Bagging on RPART In the first case, ...
2
votes
1answer
242 views

Time-series machine learning methods and R packages

I am trying to determine how to use machine learning models such as for eg., random Forest with (non-financial) time-series data. Using an example, suppose we wanted to find based on monthly scores ...
0
votes
1answer
206 views

Support Vectors Not Falling on Margin Lines for e1071 and kernlab packages in R?

In a previous thread, Computing the Decision Boundary of a linear SVM model(Computing the decision boundary of a linear SVM model), the following R code was given as a way to compute the formula of ...
0
votes
0answers
69 views

What to expect from classification models

I am testing various classification schemes on a training set with about 3000 instances and 20 attributes. The train set is distributed into 6 classes such that the chance accuracy would be about 18%. ...
2
votes
1answer
380 views

Does caret train function for glmnet cross-validate for both alpha and lambda?

Does the R caret package cross-validate over both alpha and lambda for the ...
0
votes
1answer
63 views

Priors and Loss in R

I am fairly new to R and data mining concepts and am trying to understand the rpart package in R. I am a bit confused about the role of priors and loss in the ...
1
vote
1answer
193 views

Partitional vs. hierarchical clustering with distance matrix

I am exploring the flexibility of partitional clustering algorithms. In particular, I would like to introduce more general distances than the ones which are used by default. Let us consider, for ...
2
votes
0answers
38 views

How to compute the prediction variance from Relevance Vector Machine regression

I am using a relevance vector machine in R, rvm(), to solve a regression problem. I need to know the variance of the fitted values for each identified RVs. Does anyone know how to program to compute ...
1
vote
1answer
159 views

What is the initial partition for k-means in R?

My question is probably elementary, and I apologize for that. I am reading Kogan's "Introduction to Clustering Large and High-Dimensional Data"; I am interested in understanding batch K-means and ...
1
vote
0answers
73 views

Distributed K Nearest Neighbor using RHadoop

I thought Revolution Analytics had a presentation out there about how to use RHadoop to do distributed KNN. Has anyone actually done this before, familiar with any blogs, or other references about how ...