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7 views

Can I customize preprocesses in R caret's package? [migrated]

I am using the caret package for training regressions. Since I came across of it, I knew I was gonna need it. I have looked at the section for preprocessing the ...
4
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1answer
31 views

How to train a model when instead of a target we have a range where it is?

Often in machine learning we have a situation when target is numeric (real or integer). Each target comes with an associated input vector. The goal is to learn the mapping from the input vectors to ...
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0answers
35 views

Different results from randomForest via caret and the basic randomForest package

I am a bit confused: How can the results of a trained Model via caret differ from the model in the original package? I read Issue on prediction with FinalModel of RandomForest in R using the CARET ...
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0answers
22 views

Is there any relationship between Train error and Test error in linear regression?

I am doing regularization on linear regression and am observing something arguable: By increasing the $\lambda$ (shrinkage value), I observe that there is a point in which the training and testing ...
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2answers
33 views

Should I use epochs > 1 when training data is unlimited?

If I have virtually endless training data (it's synthesized) is there still purpose in having epochs? I.e. training on the same samples multiple times?
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0answers
19 views

What is the best practices as to cropping the positive examples for training hog classifier?

I've been reading up on the literature on HOG training, but I can't figure out what the best practices are for cropping the positive examples. Question: Do you crop tight or with margins on the ...
2
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1answer
44 views

Test Error less than cross-validation error-implications?

If the test-set RMSE error of a model is less than cross-validated RMSE error, how can I interpret this? Is this abnormal? Does it imply a mistake in the methodology?
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1answer
39 views

training and testing an artificial neural network method

Is it alright to apply different epoch numbers to train/test a ANN method ( i.e. set number of iterations/epoch for training mode, and then set another different number of epoch for testing mode) ?
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0answers
27 views

Can you take a DNN that was trained without regularization, and continue training it with regularization?

If I've trained a DNN with out any regularization methods (e.g. weight decay, dropout etc.) and reached a good training error, can I somehow take that learned net and fine tune it with regularization? ...
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1answer
111 views

proportion between test and train set in regression and classification

Many claim different proportion between test and train set in regression and classification telling this should be test:train : 0.25:0.75 or 0:33:0:66 (the most popular with what I met). But what with ...
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0answers
12 views

Generating Labeled Training data from 2 data sources for Predictive Classifier

I am trying to build a predictive risk model classifier for an product (classifying good or bad). I am in the process of creating a training dataset. Here are the challenges I am facing. I have 2 ...
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1answer
69 views

How we can add new data in training time of neural network without stopping it in MATLAB?

I have a binary classification problem. Now I'm using patternnet in MATLAB R2014b to design a neural network for this problem. ...
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0answers
25 views

Adaptive Learning Rate Convolutional RBM?

I was wondering if anyone was aware of some work done for Adaptative learning rate for Convolutional RBM training ? KyungHyun Cho published an algorithm for RBM (Enhanced Gradient and Adaptive ...
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0answers
48 views

Training Neural Network with Highly Correlated Inputs

I am trying to train a basic Neural Network to predict Football final scores based on: i) Time in the match ii) Current Score iii) Parameters representing strength of home and away team. In order ...
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0answers
31 views

Honglak Lee MNIST CDBN filter shapes?

This question is based on Honglak Lee's paper "Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations". In chapter "4.3 Handwritten digit ...
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0answers
18 views

Importance of class frequency in classification

Suppose we are classifying instances into n classes that, in practice, occur at frequencies p1, p2, ... pn, (for example classifying news-articles as one of n different topics). For the purposes of ...
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1answer
52 views

Once you have a set of training data, how do you go about training a model?

I've been trying to teach myself machine learning using some books, kaggle and other resources so I'm still very new at this. I'm trying to do a competition on kaggle and I've obtained a dataset. ...
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0answers
49 views

How to choose negative training sample for Classification problem

Choosing positives sample is a relative straightforward task, but I'm having some problem on determine what should I use for the negative example. I'm working on a SVM binary classificator, trying to ...
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0answers
134 views

Pre-training deep neural networks by supervised learning

When pre-training deep neural networks layer by layer, is it normal to pre-train the layers -which haven't been pre-trained by unsupervised training- by using supervised training before we train the ...
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0answers
38 views

semisupervised classification training on all or part of unlabeled data

I have 3 sets of data. A positively labeled dataset. An unlabeled dataset that has for sure positive (around 75%) and negative data. An unlabeled dataset that has for sure positive data and maybe ...
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0answers
261 views

Tips for training dropout neural network

I use NN for my mini project research, and I found out the newest trick for feed forward NN is using dropout for regularization instead of L1/L2 norm and rectified linear unit as an activation ...
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1answer
97 views

How to compute the weights gradients for Convolutional RBM with CD?

I've successfully implemented a RBM and trained it with CD-k, but I now have some issues doing the same with Convolutional RBM. The visible and hidden biases gradients are easy to compute: v1 - v2 ...
0
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1answer
60 views

how to handle (many) false positives in training dataset for logistic regression classifier

I want to train a logistic regression dataset. I have a quite big training data set ( >100 000) and have around 10 features I can train on. Half of my training data is negative training data and I ...
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0answers
17 views

Latent semantic classification

How can I create a training data set for document classification using LSA? I have created a term-to-document matrix and have class labels also. I don't know whether to add these class labels in a ...
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1answer
293 views

How to speed up the training in neural network when mini-batch training is used?

Can anyone give me some ideas on possible techniques to speed up the training process of multilayer artificial neural network if the training involves mini-batch? So far, I understand that stochastic ...
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0answers
13 views

Speech recognition, words out of dictionary

I'm performing word recognition by using a tradional procedure. I'm extracting MFCC features. Then I'm creating a code book in order to do vector quantization. After that, I train discrete HMM for two ...
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0answers
199 views

HMM library, different length sequences training

I'm using the Kevin Murphy's HMM library in MATLAB(http://www.cs.ubc.ca/~murphyk/Software/HMM/hmm.html) There is a section called 'How to use the toolbox'. There is this example for GMM ouputs: ...
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2answers
97 views

Split train//validation/test sets by time, is it correct?

Here's the scenario, slightly altered to a common one. Credit card fraud, payments for the last 12 months (a rolling window). Train with the data from the first 10 months, validate with data from the ...
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0answers
18 views

Measures to take if activation in neural network gets saturated

I am coding an auto encoder with mnist data. It have 784 inputs, 50 hidden units, 784 outputs. Since outputs are huge in number, when error gets propagated during gradient descent, error of hidden ...
2
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2answers
98 views

Building training set from unlabeled data

I want to build classifier using naive bayes. I know that naive bayes is supervised learning that requires labeled data for training set. However, I only have data with no label on it. Is there any ...
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3answers
540 views

Neural network packages which allow shared weights and parallel training

I'm curious if there are any neural network packages out there that easily allow one to construct feed forward neural networks with shared weights, but also allow for the training to be done in ...
3
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1answer
149 views

Imputation before or after splitting into train and test?

I have a data set with N ~ 5000 and about 1/2 missing on at least one important variable. The main analytic method will be Cox proportional hazards. I plan to use multiple imputation. I will also be ...
12
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3answers
392 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 ...
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0answers
258 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 ...
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1answer
649 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
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1answer
54 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 ...
1
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0answers
248 views

CV.glmnet results [duplicate]

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 ...
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1answer
1k 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 ...
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0answers
89 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
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1answer
104 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
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1answer
455 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 ...
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0answers
307 views

Metric warning using caret's rfe

I am using the caret package to do feature selection with rfe while training a knn ...
2
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2answers
73 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
663 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
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1answer
586 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: ...
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2answers
262 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
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1answer
218 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
123 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
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0answers
97 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. ...
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2answers
183 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 ...