Practical Machine Learning with R and Python – Part 5

(This article was first published on R – Giga thoughts …, and kindly contributed to R-bloggers) This is the 5th and probably penultimate part of my series on ‘Practical Machine Learning with R and Python’. The earlier parts of this series included 1. Practical Machine Learning with R and Python – Part 1 In this initial…

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Ensemble learning for time series forecasting in R

(This article was first published on Peter Laurinec, and kindly contributed to R-bloggers) Ensemble learning methods are widely used nowadays for its predictive performance improvement. Ensemble learning combines multiple predictions (forecasts) from one or multiple methods to overcome accuracy of simple prediction and to avoid possible overfit. In the domain of time series forecasting, we…

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Practical Machine Learning with R and Python – Part 2.

(This article was first published on R – Giga thoughts …, and kindly contributed to R-bloggers) In this 2nd part of the series “Practical Machine Learning with R and Python – Part 2”, I continue where I left off in my first post Practical Machine Learning with R and Python – Part 2. In this post…

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Practical Machine Learning with R and Python – Part 1

(This article was first published on R – Giga thoughts …, and kindly contributed to R-bloggers) Introduction This is the 1st part of a series of posts I intend to write on some common Machine Learning Algorithms in R and Python. In this first part I cover the following Machine Learning Algorithms Univariate Regression Multivariate…

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Using regression trees for forecasting double-seasonal time series with trend in R

(This article was first published on Peter Laurinec, and kindly contributed to R-bloggers) After blogging break caused by writing research papers, I managed to secure time to write something new about time series forecasting. This time I want to share with you my experiences with seasonal-trend time series forecasting using simple regression trees. Classification and…

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Estadística y Machine Learning con R

Introducción

Capítulo I: Modelo lineal general.

Capítulo II: Extensiones al modelo de regresión lineal

Capítulo III: Modelos con Variables Cualitativas

Capítulo IV: Métodos de clasificación

Capítulo V: Agrupación de la información

Capítulo VI: Inferencia no parámetrica

Bilbliografía

 

Stock Trading Analytics and Optimization in Python with PyFolio, R’s PerformanceAnalytics, and backtrader.

(This article was first published on R – Curtis Miller’s Personal Website, and kindly contributed to R-bloggers) Introduction Having figured out how to perform walk-forward analysis in Python with backtrader, I want to have a look at evaluating a strategy’s performance. So far, I have cared about only one metric: the final value of the…

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