How to Use Pandas Query
This tutorial will show you how to use the Pandas query method to subset your data. The tutorial will explain the syntax and also show you step-by-step examples of how...continue reading.
This tutorial will show you how to use the Pandas query method to subset your data. The tutorial will explain the syntax and also show you step-by-step examples of how...continue reading.
Bootstrapping time series? It is meant in a way that we generate multiple new training data for statistical forecasting methods like ARIMA or triple exponential smoothing (Holt-Winters method etc.) to...continue reading.
Inspired by recent headlines like “Fear Overtakes Greed in IPO Market after WeWork Debacle” and “This Year’s IPO Class is Least Profitable since the Tech Bubble”, today we’ll explore historical...continue reading.
Hello and welcome to this new issue! Release Date: 2019-10-21 This week’s release was curated by Colin Fay, with help from the RWeekly team members and contributors. Highlight A golem...continue reading.
In the post https://statcompute.wordpress.com/2019/10/13/assess-variable-importance-in-grnn, it was shown how to assess the variable importance of a GRNN by the decrease in GoF statistics, e.g. AUC, after averaging or dropping the variable...continue reading.
The function grnn.margin() (https://github.com/statcompute/yager/blob/master/code/grnn.margin.R) was my first attempt to explore the relationship between each predictor and the response in a General Regression Neural Network, which usually is considered the Black-Box...continue reading.
Jumping Rivers is a data science consultancy company focused on R and Python. We work across industries and throughout the world. We offer a mixture of training, modelling, and infrastructure...continue reading.
rBokeh is an interactive plotting library. Since it functions lack some arguments compared to its Python counterpart, plots are sometimes difficult to customize. I will show how to overcome those...continue reading.
Producing an API that serves model results or a Shiny app that displays the results of an analysis requires a collection of intermediate datasets and model objects, all of which...continue reading.
The new package discrim contains parsnip bindings for additional classification models, including: Linear discriminant analysis (LDA, simple and L2 regularized) Regularized discriminant analysis (RDA, via Friedman (1989)) Flexible discriminant analys…continue reading.
Another very low-key arithmetic problem as Le Monde current mathematical puzzle: 32761 is 181² and the difference of two cubes, which ones? And 181=9²+10², the sum of two consecutive integers....continue reading.
Long time no see, Statisfaction! I’m glad to write about my habilitation entitled Bayesian statistical learning and applications I defended yesterday at Inria Grenoble. This Habilitation à Diriger des Recherches...continue reading.
TL;DR Why use object-oriented programming in Shiny applications? It’ll help organizize organize the code in your application! Organize Your Shiny Code with Object-Oriented Programming Classes are used widely in all...continue reading.
At Mango, we firmly believe that any decision can be better made using analytics and data. We also know that a company’s success is increasingly dependent on becoming data-driven. That’s...continue reading.
Riinu and I are sitting in Frankfurt airport discussing the paper retracted in JAMA this week. During analysis, the treatment variable coded [1,2] was recoded in error to [1,0]. The...continue reading.
In the post (https://statcompute.wordpress.com/2017/01/08/an-example-of-merge-layer-in-keras), it was shown how to build a merge-layer DNN by using the Keras Sequential model. In the example below, I tried to scratch a merge-layer DNN...continue reading.
This article is originally published at https://lcolladotor.github.io/ Thanks for visiting r-craft.org This article is originally published at https://lcolladotor.github.io/ Please visit source website for post related comments.continue reading.
Shiny 1.4.0 has been released! This release mostly focuses on under-the-hood fixes, but there are a few user-facing changes as well. If you’ve written a Shiny app before, you’ve probably...continue reading.
Shiny 1.4.0 has been released! This release mostly focuses on under-the-hood fixes, but there are a few user-facing changes as well. If you’ve written a Shiny app before, you’ve probably...continue reading.
This tutorial will explain the NumPy empty function (AKA np.empty) and will show you how to create an empty array in NumPy. The tutorial assumes that you have somewhat limited...continue reading.