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Results tagged with Search options user 32397

Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

0
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2answers
Why is direct sampling from the posterior distribution intractable?
asked Jan 2 '14 by user2806363
50
votes
5answers
I'm building regression models. As a preprocessing step, I scale my feature values to have mean 0 and standard deviation 1. Is it necessary to normalize the target values also?
asked Aug 11 '14 by user2806363
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3answers
I have clustering algorithm and I cluster labelled data sets to see my clustering algorithm performs. I was thinking to report performance of my clustering in sense of some score, like RandIndex scor …
asked Nov 1 '17 by user2806363
2
votes
1answer
Can anybody explain what multitask learning is in an intuitive way? From Wiki: Multitask learning aims to improve the performance of learning algorithms by learning classifiers for multiple ta …
asked Jan 8 '14 by user2806363
0
votes
1answer
I have four nested models.Every of them learned from different data sets. now I want to compare these models together.normally people try to compute the F-satistics. But for my case, it's bit harder, …
asked Jul 22 '14 by user2806363
1
vote
0answers
I have two models from two different data sets. Model 1 contain 50 features and model 2 contain 40 features. the intersection of features of model 1 and 2 is 10. so how can I assess the relative impor …
asked Jul 23 '14 by user2806363
2
votes
1answer
I'm training the self organizig map, I need to set the value for the radius of it. is there any method to find the optimum radius size ?
asked Jan 7 '14 by user2806363
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1answer
I want to construct Bayesian network for a 800 genes(genes are my node/variables). I have only 30 cancer samples and 30 normal sample. So I want to create network for cancer samples and for the norma …
asked Jan 18 '14 by user2806363
0
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0answers
I have learned lot's of Lasso regression models(20000) using glmnet. I need to compute somehow test statistics for each features of models. like F-statistics,... Can I do this using bootstrapping ? i …
asked Oct 14 '14 by user2806363
0
votes
1answer
I have N graphs, they all have same topology,but they differ in vertices weight. I would like to cluster these graphs such that graphs that their vertices has similar weights in similar positions are …
asked Oct 14 '17 by user2806363
0
votes
0answers
I have a feature matrix, where the columns correspond to the features and the rows are the data points. My matrix is zero-inflated, meaning there are many false-negative zero entries in my matrix. I …
asked Jul 17 by user2806363
4
votes
2answers
I have problem in intuitive understanding of following arguement: "The trees generated via bagging are identically distributed, thus the expectation of the average of a set of trees is the same as th …
asked Mar 6 '14 by user2806363
3
votes
0answers
I have learned many models and I calculated p-values for the cross-validation errors. I want to select significant models based on the false discovery rate (FDR). How can I estimate the FDR from p-val …
asked Mar 13 '14 by user2806363
4
votes
2answers
I have read about the fact that, there is dependency of variance on mean of count data.In most of cases they do variance stabilization transfomration as preprocessing step of data modeling. I wonder, …
asked Aug 14 '14 by user2806363
3
votes
1answer
I have two different regression models which I learned from two different data sets. Is there any statistical method which shows the significance of models based on the number of parameters and cross …
asked Jun 23 '14 by user2806363

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