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Questions related to Statistical Learning

I have a dataset with 19 training points and 6 testing points. At first I defined the rules for 19 training sets and then tried making predictions for the rest of 6 points. But I got all constant...

06 January 2021 3,866 5 View

In Statistical Learning Theory, Uniform convergence means for a hypothesis class H, given m(\delta, \epsilon), for arbitrary distribution over domain (X, Y), with probability $1- \delta$, the...

03 November 2020 7,809 5 View

For example; can the dynamical systems theory help us find underlying general structures of the systems to make more accurate models?. Perhaps some data reflect these structures that are not...

08 September 2019 9,460 1 View

05 September 2019 4,009 1 View

Bayesian updating and and Bayesian networks are used in so many machine learning algorithms, but can we consider them as machine learning techniques? and if we can, under what circumstances? and...

05 June 2019 6,049 6 View

01 June 2019 9,430 5 View

I am university student and my bachelor thesis is Diabetes Pre-diagnostics with Statistical Learning. I need dataset including items of common risk factors of diabetes. Is there someone who could...

10 November 2018 3,603 9 View

We have conducted study with intervention of exercise to measure muscle strength (6 variables) and balance (3 variables). The measurements had been taken at 5 regular intervals (pre, post 1, post...

06 July 2018 3,630 6 View

I want to know different sampling strategies to understand big data. Or statistical learning with respect to big data

05 June 2018 2,036 1 View

Is there any literature that focuses on design of the classifier theoretically, without considering metrics.

02 March 2018 5,317 4 View

The Big Data revolution promises to transform how we live, work, and think by enabling process optimization, empowering insight discovery and improving decision making. The realization of this...

11 December 2017 2,640 3 View

I wonder if there is any explanation that which of statistical learning or machine learning may work better and what is reason for that.

10 November 2017 9,706 9 View

Please write me pro and contra arguments!

07 August 2017 9,480 2 View

31 July 2017 918 2 View

The aspect of over-fitting is typically viewed from the perspective of both- accuracy and model complexity. To mitigate over-fitting, we usually have the practical approach of having k-fold...

04 May 2017 1,077 1 View

As the title, I am learning Bayesian method now. Previously, I preferred to use prediction regarding to a concrete machine learning problem, but I found out that people usually use 'inference' in...

03 April 2017 4,197 0 View

Hello, I am searching for a good Bayesian book for someone who has good notions about statistics but never realy learned inferential statistics. Does anybody know a good book to get started with...

02 March 2017 3,721 3 View

I know I may be asking for the moon, but does anyone know of a statistical learning task that is fast to administer (around 5 minutes or less) and that has high(ish) reliability?

10 November 2016 8,454 0 View

If the data for the classes is imbalanced what are the best machine learning algorithms and will he choice vary in the case of binary and multi-class classification

08 June 2016 514 5 View

05 June 2016 7,282 6 View

Does anyone have a graphical representation/explanation of the difference between ANOVA, ANCOVA, MANOVA and MANCOVA?

10 May 2016 9,616 3 View

04 May 2016 4,818 4 View

Hi researchers! I am a learner of statistics learing and machine learning. After applying the Convolutional neural networks into image recognition and text mining, I think this method is powerful...

05 March 2016 3,265 7 View

02 March 2016 8,249 5 View