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10
votes
3answers
160 views

Training, testing, validating in a survival analysis problem

I've been browsing various threads here, but I don't think my exact question is answered. I have a dataset of ~50,000 students and their time to dropout. I am going to be performing proportional ...
1
vote
0answers
34 views

k-means + linear regression: How to split the data for validation

I want to cluster my data first using k-means and then determine a regression model for each cluster. Then I want to evaluate the performance of this approach using split validation. I can think of ...
3
votes
1answer
51 views

How to perform parameters tuning for machine learning?

I have a very basic question regarding parameter tuning using grid search. Typically some machine learning methods have parameters that need to be tuned using grid search. For example, in the ...
0
votes
0answers
18 views

Appropriate bounding boxes on images for training data?

This is the first time I'm doing research in computer vision, and I'm going to be using OpenCV's cascaded training, for which I'm preparing positive samples for training data. If anyone's experienced ...
0
votes
1answer
30 views

Improvement on duplicating instances

I have a task of Relationship extraction. There are some set of predefined relations in the corpus. I need to train classifier to recognize the type of relation or the lack of relation between every ...
0
votes
0answers
92 views

CV.glmnet results

I was working through the lab on ridge regression and LASSO in ISLR and I came across a strange behavior in the cv.glmnet function. When I followed the lab as ...
1
vote
1answer
177 views

What is the best strategy to train and validate classification using PLS-[classifier] in caret package?

I have 4 clusters (see plot below) extracted from data of medical samples N=218 measured for 11 genes/predictors P=11 by this ...
0
votes
0answers
27 views

positive samples in dataset for classifier training - how should environment figure in?

I have a question about preparing the dataset of positive samples for a cascaded classifier that will be used for object detection. As positive samples, I have been given 3 sets of images: a set of ...
1
vote
0answers
70 views

3D Gaussian basis function

I need tο use 3D data for training and for that I need to find the Gaussian basis function. I know how to find $f(x,y)$ but how can I find $f(x,y,z)$?
1
vote
1answer
98 views

Linear regression from data that don't represent a function

I have $(x,\ y)$ pairs with a strongly suspected linear correlation. So I want to fit the "best" linear function in order to make predictions for unknown $x$'s. These pairs don't represent a function, ...
1
vote
1answer
211 views

Data split into training and test

I am implementing an EEG classifier with 15 subjects (patients), specifically a support vector machine classifier. I randomly choose the training and testing sets, but I was faced by a question "how ...
0
votes
0answers
102 views

Metric warning using caret's rfe

I am using the caret package to do feature selection with rfe while training a knn ...
2
votes
2answers
63 views

Is it always bad to retrain your model to include predicted data?

I understand intuitively why this is a horrible idea - you assume your model is correct and then increase your number of observations which will likely result in a poor fit on future data. I'm ...
1
vote
1answer
192 views

R caret difference between ROC curve and accuracy for classification

In case of caret package test function metric option, one can use either accuracy or ROC as a metric that will be used to finalize values of tuning parameters. I felt that accuracy and ROC are the ...
1
vote
1answer
243 views

LGOCV caret package R

i am learning data mining through book . During classification chapters about Neural Networks the authors have below code. I have below questions: ...
0
votes
2answers
88 views

Text Annotation tools

I have tried open nlp NER for extracting organization names with not great success (It could be model is not fit for the domain I am working). So, I am planning to train Open NLP NER on my training ...
3
votes
1answer
149 views

Feature selection in the training set

I have a classifier, and I am using leave one out cross-validation to assess its performance. On each iteration, I divide the dataset into training and testing sets. The testing set is just the ...
3
votes
1answer
88 views

Methods for time-series prediction depending on multiple parameters

We have hourly time-series data of the status of a system: number of people present at different train stations. We collected it for a year, and we want to use it to train a model to predict the ...
0
votes
0answers
77 views

Forming training set for Multinomial Naive Bayes

Is it true that Multinomial Naive Bayes requires equally by count training data for each class to get best performance? For example, we forming classifier for three classes - Japan, China, Korea. ...
1
vote
2answers
157 views

Combining labeled and unlabeled data for training

When training my algorithm, if I can get some i.e. data my future test data that has no labels can it improve my algorithm's efficiency, is there any mathematical proof for it? PS: I think ...
3
votes
0answers
268 views

Logistic Regression Cost Function issue in Matlab

I'm trying to implement a logistic regression function in matlab. I calculated the theta values, linear regression cost function is converging and then I use those parameters in logistic regression ...
3
votes
1answer
203 views

SVM retrain on whole dataset for final model --> overfitting?

i am training a SVM (RBF kernel) with a dataset of ~1500 samples (balanced) using fminsearch on the CV error for parameter optimization (C and s). After i found the "best" parameters (local optima ...
0
votes
1answer
156 views

What is Generalization errror on training set. How can I see it on weka?

I get output like this .. ...
1
vote
1answer
368 views

Can a neural network output represent a posterior probability?

I seem to remember from years ago when I first read Bishop's ANN book that it is possible to construct a neural network such that the outputs should represent the posterior probability that I would ...
5
votes
5answers
868 views

Is using the same data for feature selection and cross-validation biased or not?

We have a small dataset (about 250 samples * 100 features) on which we want to build a binary classifier after selecting the best feature subset. Lets say that we partition the data into: Training, ...
1
vote
1answer
154 views

Machine Learning and training time: is it really relevant?

I have a question regarding the time needed for training a classifier. I am facing the specific problem of Sentiment Analysis (classification of text as pos/neg/neu). (Excepting online learning ...