[morpheus.git] / vignettes / report.Rmd

---
title: morpheus...........

output:
  pdf_document:
    number_sections: true
    toc_depth: 1
---

```{r setup,  results="hide", include=FALSE}
knitr::opts_chunk$set(echo = TRUE, include = TRUE,
  cache = TRUE, comment="", cache.lazy = FALSE,
  out.width = "100%", fig.align = "center")
```

0) Tell that we try to learn classification parameters in a non-EM way, using algebric manipulations.

*morpheus* is a contributed R package which attempts to find the parameters of a mixture of logistic classifiers.
When the data under study come from several groups that have different characteristics, using mixture models is a very popular way to handle heterogeneity.
Thus, many algorithms were developed to deal with various mixtures models. Most of them use likelihood methods or Bayesian methods that are likelihood dependent.
*flexmix* is an R package which implements these kinds of algorithms.

However, one problem of such methods is that they can converge to local maxima, so several starting points must be explored.
Recently, spectral methods were developed to bypass EM algorithms and they were proved able to recover the directions of the regression parameter
in models with known link function and random covariates (see [9]).
Our package extends such moment methods using least squares to get estimators of the whole parameters (with theoretical garantees, see [XX]).
Currently it can handle only binary output $-$ which is a common case.

1) Model.

TODO: retrouver mon texte initial + article.

2) Algorithm (as in article)

3) Experiments: show package usage
Commit	Line	Data
3d5b5060 BA	1	---
	2	title: morpheus...........
	3
	4	output:
	5	pdf_document:
	6	number_sections: true
	7	toc_depth: 1
	8	---
	9
	10	```{r setup, results="hide", include=FALSE}
	11	knitr::opts_chunk$set(echo = TRUE, include = TRUE,
	12	cache = TRUE, comment="", cache.lazy = FALSE,
	13	out.width = "100%", fig.align = "center")
	14	```
	15
	16	0) Tell that we try to learn classification parameters in a non-EM way, using algebric manipulations.
3d5b5060	17
cff1083b BA	18	morpheus is a contributed R package which attempts to find the parameters of a mixture of logistic classifiers.
	19	When the data under study come from several groups that have different characteristics, using mixture models is a very popular way to handle heterogeneity.
	20	Thus, many algorithms were developed to deal with various mixtures models. Most of them use likelihood methods or Bayesian methods that are likelihood dependent.
	21	flexmix is an R package which implements these kinds of algorithms.
3d5b5060	22
cff1083b BA	23	However, one problem of such methods is that they can converge to local maxima, so several starting points must be explored.
	24	Recently, spectral methods were developed to bypass EM algorithms and they were proved able to recover the directions of the regression parameter
	25	in models with known link function and random covariates (see [9]).
	26	Our package extends such moment methods using least squares to get estimators of the whole parameters (with theoretical garantees, see [XX]).
	27	Currently it can handle only binary output $-$ which is a common case.
3d5b5060	28
cff1083b	29	1) Model.
3d5b5060	30
cff1083b	31	TODO: retrouver mon texte initial + article.
3d5b5060	32
cff1083b	33	2) Algorithm (as in article)
3d5b5060	34
cff1083b	35	3) Experiments: show package usage