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4
votes
5answers
359 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, ...
3
votes
0answers
190 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 ...
2
votes
1answer
106 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 ...
1
vote
2answers
137 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 ...
1
vote
1answer
112 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 ...
1
vote
1answer
129 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 ...
0
votes
0answers
53 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.
...
0
votes
0answers
77 views
What is Generalization errror on training set. How can I see it on weka?
I get output like this ..
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0
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0answers
53 views
What are origin/rationales for standard training vs. test data splits?
In experiments on supervised learning using a held out test set, one commonly sees allocations of labeled examples ranging from 50% training/50% test up to 80% training/20% test. These proportions ...
