training (or estimation) of statistical models or algorithms.

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7 views

Almost a multinomial logistic regression

Is there a way to train a multinomial logistic model where the true classification is unknown, but summary information obtained from the true classifications is known? Illustrative Example: 5 ...
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21 views

What is the minimum sample size required to train a Deep Learning model - CNN?

It is true that the sample size depends on the nature of the problem and the architecture implemented. But, on average, what is the typical sample size utilized for training a deep learning framework? ...
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20 views

The meaning of “training accuracy”?

If I split my data set into testing, training (further separated into subtraining and validation data set in cross-validation). In the context of machine learning and esp. in those ROC comparing the ...
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2answers
49 views

How to create a variable that is present in test data set but not in train?

Im try to do a classification but i have a variable production budget which is present in test dataset and not in train. so how do i proceed. could i impute that variable somehow. i dont want to drop ...
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1answer
79 views

How do I use deep learning (Convolution Neural Network) with small training data-set?

I have an image data set of around 180 images in 60 classes (3 images per class). I am able to build a classifier using feature matching. However, I want to try Convolution Neural Networks and see if ...
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0answers
17 views

How do I consider the whole training set in the process of Hidden Markov Model training?

I'm trying to train a Hidden Markov Model following theory from the book "Pattern Classification" by Duda, Hart, and Sotrk. For the HMM learning they discuss Forward-Backward algorithm there, ...
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1answer
23 views

Can I use cross validation on a subset of the training set to select hyperparameters?

I am using R, and I had a dataset with 400000 rows and 800 columns, training a random forest model with only 100 trees on this dataset will take me about 1 and half hour on my laptop. So I went on and ...
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3answers
69 views

Why does the training error usually underestimate the test error?

I understand that most algorithms are optimized to minimize the training error but why is the test error usually larger then the training error? Is there a statistical reason why?
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1answer
35 views

Real world model training in R: how to get instant feedback?

I want to train a model. I can just randomly choose method (e.g. random forest), put whole dataset, wait a few hours, check accuracy, plot every possible curve (like accuracy vs train size) and see ...
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4answers
247 views

Does increase in training set size help in increasing the accuracy perpetually or is there a saturation point?

I am using a boosted trees classifier which is giving better accuracy then all other linear classifier I tried. I have almost an unlimited training data at my disposal , I wanted to know if there is a ...
4
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1answer
119 views

ML / train-test-validate: What is allowed when?

As someone getting started in machine learning, I am trying to get my head around the rules / good practices to follow when building, testing and validating supervised ML models in order not to ...
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1answer
43 views

Logistic Regression with empty cells

I have a data set from which I need to train a model and use it for prediction. Let's say I want to predict what people say about food items produced by a cake shop. Let's assume people have stated ...
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1answer
42 views

Feeding categorical data to classifier

Suppose I have the dataset in the following format: ...
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2answers
59 views

Trying to understand how I should split data between (train and test) Vs. predict?

I'm working on a model to predict churn. I understand the concept of training and testing, or at least I thought I did. Let's say it's the first of the month and our database has 10,000 subscribers, ...
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0answers
52 views

GBM Performance on different sampling techniques

I am working on a healthcare data set for breast cancer patients. This data set is class imbalances and the distribution of positive and negative classes is 80%/20%. In order to deal with the class ...
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3answers
81 views

splitting a training data set based on classifier accuracy

I have training data with ~600K instances. If I split the training data into four segments and build four separate classifiers, I get much higher accuracy for each model than if I train a single model ...
3
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1answer
75 views

Minimum length of training data?

I want to obtain a prediction model using support vector regression on a time series data set. In literature, I have read that the break up ratio for training/testing/validation of data should be ...
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2answers
107 views

How to formulate data for neural network with “class” inputs and a numerical output

I'm just starting to play with neural networks (via PyBrain). I've got some questions about problem formulation. I've taken a bunch of rugby data (very topical), ...
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1answer
139 views

How to train a Gaussian mixture hidden markov model

I want to build a hmm with continuous observations modeled as Gaussian mixtures. The way I understand the training process is that it should be made in 2 steps. 1) Train the GMM parameters first ...
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1answer
83 views

Inverse progression for training & validation data during training with H2O

I'm training on a dataset with 3600 columns. 100948 training rows & 25238 validation rows. These are the R commands I'm using: ...
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50 views

How to train radial basis function for function approximation?

There is an Autoregressive model of order 1 (AR(1)) that is excited by a non-linear signal as the input: $$x_t = \rho x_{t-1} + u_t \tag{1}$$ The time series $u_t$ is generated from a Mackey-Glass ...
1
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1answer
86 views

Is this training dataset enough for training and testing classification model?

My training dataset contains just 2 classes with 40 features. In case 1, class 1 has 35 samples and class 2 has 700 samples. In case 2, class 1 has 65 samples and class 2 has the same value as ...
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0answers
44 views

Training set selection

I have the following question for a project I'm working on. I am trying to find the best strategy to select the best training set in a dataset. I have a dataset with a few billions rows. I am trying ...
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1answer
111 views

Creating a test set with imbalanced data

I am working on a binary random forest using R. mu data set consists of 300 cases classes 1 and 2100 cases class 0. I am planning to evaluate my model using the model prediction and the AUC and for ...
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0answers
64 views

too many ties in knn? how to solve this problem

I use the knn model to train my data and then eliminate accuracy via cross-validation, but when I use the following code, I get the error: ...
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0answers
33 views

How to detect contradictory examples in training data

I want to implement an online learning classification algorithm. Therefore I want to detect contradictory examples in my training data once the user wants to add a new example to the training data. ...
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106 views

TfidfVectorizer: should it be used on train only or train+test

When training a model it is possible to train the Tfidf on the corpus of only the training set or also on the test set. It seems not to make sense to include the test corpus when training the model, ...
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0answers
206 views

Random Forest online/incremental learning in R

Is there a Random Forest implementation available in R, that supports online learning? My alternative approach was to use the popular randomForest package and combine Random Forests (the existing one ...
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123 views

Test MAPE < Train MAPE using auto.arima()

I am trying to build a forecasting model for the passenger vehicles registrations in a given country, and I wanted to use $auto.arima$ function from the $forecast$ package to estimate a simple ARIMA ...
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0answers
24 views

Should the number of normal samples always be more than that of anomalous samples in training set for anomaly detection?

I am trying to train an anomaly detection algorithm (one-class svm) on a data set with a few hundred positive samples and several thousands negative examples. Is it mandatory that I train the model ...
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0answers
24 views

Which phrase is correct? “Out of sample” or “Hold out sample”?

Which one is correct phrase for data that model didn't see? For example i trained my model based on data-set from 200 to 2002. Now i want test my model using 2003 data-set. Which phrase is correct in ...
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1answer
191 views

Extracting Standard Errors Caret Model

I have tuned a glm net model with caret using the train function. I am trying to extract the coefficients and standard errors of those coefficients for the best tuned model. Following this CV post I ...
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0answers
199 views

In machine learning, may I train correctly a neural network with input real data and output validation Boolean data?

I have a matrix made of ~ 100 rows and 12 columns. Each entry contains a real value. The first 6 columns refer to a particular concept (firstClass), the following 6 to another one (secondClass), and ...
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0answers
18 views

Learning over Multinomial data

I have a training data with 68 features... Each of which is a different multinomial distribution. Eg. Feature 1 can take 1 of 4 values while feature 2 can take one of 10 values. Which classifier or ...
5
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1answer
249 views

Card Games and Neural Network Inputs

Looking for some pointers on how best to structure a neural net that deals with a card game. In Gin (rummy), you have a 10-card hand and you're trying to make melds and sets out of your cards. A meld ...
0
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1answer
46 views

Cross-Validation in binary classification using only 10 positive samples (SVM)

I have a binary classification problem for which only $10$ positive samples are available for training. Negatives are in general in abundance, but I choose to use solely $70$ ($7$ negatives per one ...
0
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1answer
159 views

How to divide dataset into training and test set in Recommender Systems?

I am working on two simple recommender systems - Collaborative (item-item a user-user) and Content Based. I would like to evaluate prediction accuracy of these systems. I am used to divide dataset ...
4
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1answer
93 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 ...
4
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0answers
3k 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
108 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 ...
2
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2answers
101 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
34 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
326 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?
0
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1answer
284 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
100 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? ...
3
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1answer
262 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 ...
0
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1answer
359 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
54 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
166 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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1answer
65 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. ...