2372 search results for "regression"

Microeconomic Theory and Linear Regression (Part 2)

April 21, 2017
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Microeconomic Theory and Linear Regression (Part 2)

Introduction In the first part of this article I explained and compared four different functional forms to model apples' production. This is what I need to retake the previously explained examples: # Libraries #install.packages(c("micEcon","lmtest","bbmle","miscTools")) library(micEcon) library(lmtest) library(stats4) #this is a base package so I don't install this library(bbmle) library(miscTools

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Logistic regressions (in R)

April 21, 2017
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Logistic regressions are a great tool for predicting outcomes that are categorical. They use a transformation function based on probability to perform a linear regression. This makes them easy to interpret and implement in other systems. Logistic regressions can be The post Logistic regressions (in R) appeared first on Locke Data. Locke Data are a data...

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Hybrid content-based and collaborative filtering recommendations with {ordinal} logistic regression (2): Recommendation as discrete choice

April 14, 2017
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Hybrid content-based and collaborative filtering recommendations with {ordinal} logistic regression (2): Recommendation as discrete choice

In this continuation of “Hybrid content-based and collaborative filtering recommendations with {ordinal} logistic regression (1): Feature engineering” I will describe the application of the {ordinal} clm() function to test a new, hybrid content-based, collaborative filtering approach to recommender engines by fitting a class of ordinal logistic (aka ordered logit) models to ratings data from...

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Hybrid content-based and collaborative filtering recommendations with {ordinal} logistic regression (1): Feature engineering

April 14, 2017
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Hybrid content-based and collaborative filtering recommendations with {ordinal} logistic regression (1): Feature engineering

I will use {ordinal} clm() (and other cool R packages such as {text2vec} as well) here to develop a hybrid content-based, collaborative filtering, and (obivously) model-based approach to solve the recommendation problem on the MovieLens 100K dataset in R. All R code used in this project can be obtained from the respective GitHub...

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Microeconomic Theory and Linear Regression (Part 1)

April 14, 2017
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Microeconomic Theory and Linear Regression (Part 1)

Introduction Last week I found a lot of materials I used as teaching assistant. Among those materials I found some class notes from Arne Henningsen, the author of micEcon R package. I'll use that package and some others to show some concepts from Microeconomic Theory. Packages installation: #install.packages(c("micEcon","lmtest","bbmle","miscTools")) library(micEcon) library(lmtest) library(stats4) #this is a...

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Microeconomic Theory and Linear Regression (Part 1)

April 14, 2017
By
Microeconomic Theory and Linear Regression (Part 1)

Introduction Last week I found a lot of materials I used as teaching assistant. Among those materials I found some class notes from Arne Henningsen, the author of micEcon R package. I'll use that package and some others to show some concepts from Microeconomic Theory. Packages installation: #install.packages(c("micEcon","lmtest","bbmle","miscTools")) library(micEcon) library(lmtest) library(stats4) #this is a...

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How and when: ridge regression with glmnet

April 10, 2017
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How and when: ridge regression with glmnet

@drsimonj here to show you how to conduct ridge regression (linear regression with L2 regularization) in R using the glmnet package, and use simulations to demonstrate its relative advantages over ordinary least squares regression.  Ridge regression Ridge regression uses L2 regularisation to weight/penalise residuals when the parameters of a regression model are being learned. In the context of...

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April R Course Finder update: Logistics Regression, New platforms and Complete Machine Learning

April 9, 2017
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April R Course Finder update: Logistics Regression, New platforms and Complete Machine Learning

Last year we launched R Course Finder, an online directory that helps you to find the right R course quickly. With so many R courses available online, we thought it was a good idea to offer a tool that helps people to compare these courses, before they decide where to spend their valuable time and Related exercise sets:

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Fitting a rational function in R using ordinary least-squares regression

April 6, 2017
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Fitting a rational function in R using ordinary least-squares regression

by Srini Kumar, VP of Product Management and Data Science, LevaData; and Bob Horton, Senior Data Scientist, Microsoft A rational function is defined as the ratio of two functions. The (https://en.wikipedia.org/wiki/Pad%C3%A9_approximant) uses a ratio of polynomials to approximate functions: $$ R(x)= \frac{\sum_{j=0}^m a_j x^j}{1+\sum_{k=1}^n b_k x^k}=\frac{a_0+a_1x+a_2x^2+\cdots+a_mx^m}{1+b_1 x+b_2x^2+\cdots+b_nx^n} $$ Here we show a way to fit this type of...

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Linear regression in “The Man who counted”

March 25, 2017
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Linear regression in “The Man who counted”

Recently, I got a book by Brasilian writer  Júlio César de Mello e Souza (published under pen name Malba Tahan), titled The Man who counted. Book is a collection of mathematical stories very similar to Scheherazada’s 1001 Nights, where mathematical story-telling is the center of book.                                                In story 5“In so many words”, Malba describes … Continue...

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