Questions tagged [non-parametric]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
3
votes
2answers
85 views

How do you use KS-test in a data science report?

I'm writing a data science report, I want to find an exist distribution to fit the sample. I got a good looking result , but when I use KS-test to test the model, I got a low p-value,1.2e-4, ...
1
vote
1answer
28 views

what are the main differences between parametric and non-parametric machine learning algorithms?

I am interested in parametric and non-parametric machine learning algorithms, their advantages and disadvantages and also their main differences regarding computational complexities. In particular I ...
0
votes
2answers
30 views

Books about statistical inference [closed]

I'm currently taking a course "Introduction to Machine Learning" which covers the following topics: linear regression, overfitting, classification problems, parametric & non-parametric ...
0
votes
1answer
40 views

Logic behind the Statement on Non-Parametric models

I am currently reading 'Mastering Machine Learning with scikit-learn', 2E, by Packt. In Lazy Learning and Non-Parametric models topic in Chapter 3- Classification and Regression with k-Nearest ...
1
vote
1answer
43 views

Do non-parametric models always overfit without regularization?

Let's scope this to just classification. It's clear that if you fully grow out a decision tree with no regularization (e.g. max depth, pruning), it will overfit the training data and get full accuracy ...
0
votes
1answer
15 views

pass variable length argument to mstats.kruskalwallis

I am trying to run kruskawallis test on multiple columns of my data for that i wrote an function ...
1
vote
2answers
123 views

Linear vs Non linear regression (Basic Beginner)

So my doubt is basically in Linear regression, We try to fit a straight line or a curve for a given training set. Now, I believe whenever the features (independent variable) increases, parameters also ...
1
vote
1answer
37 views

About confidence/prediction intervals: parametric methods VS non-parametric (via bootstrap) methods

About the methodology to find confidence and/or prediction intervals in, let's say, a regression problem, I know 2 main options: Checking normality in the estimates/predictions distribution, and ...
1
vote
0answers
11 views

Non-parametric regression on set of time series: One model for each or one for all series?

Let's say I have a set of 1D time series which values have been samples in equip-distant time steps with timestamps $1,2,3,...$, they have all the same lengths and are somewhat similar in shape. I ...
5
votes
3answers
1k views

Should features be correlated or uncorrelated for classification?

I have seen researchers using pearson's correlation coefficient to find out the relevant features -- to keep the features that have a high correlation value with the target. The implication is that ...
0
votes
1answer
114 views

The distribution of dataset train and test are the differents, how to fix this?

I am new in data science and like some help to understand my problem. For instance, I have two signals non-stationary for the same condition (figure 1). I acquisition them at different times(in the ...
2
votes
1answer
27 views

Good introductory reference for Bayesian Non-parametric (Dirichlet Process / Chinese Restaurant Process)

I am looking for a recommendation for basic introductory material on Bayesian Non-parametric methods, specifically Dirichlet Process / Chinese Restaurant Process. I am looking for material which ...