- How to use linear regression forecast indicator install#
- How to use linear regression forecast indicator code#
- How to use linear regression forecast indicator plus#
A new version of nnetsauce, and a new Techtonique website Sep 11, 2020. Forecasting lung disease progression Oct 2, 2020. Simulation of dependent variables in ESGtoolkit Oct 9, 2020. Submitting R package to CRAN Oct 16, 2020. A glimpse into my PhD journey Oct 23, 2020. 
Statistical/Machine Learning explainability using Kernel Ridge Regression surrogates Nov 6, 2020. Boosting nonlinear penalized least squares Nov 21, 2020. Generalized nonlinear models in nnetsauce Nov 28, 2020. Bayesian forecasting for uni/multivariate time series Dec 4, 2020. Classify penguins with nnetsauce's MultitaskClassifier Dec 11, 2020. A deeper learning architecture in nnetsauce Dec 18, 2020. 2020 recap, Gradient Boosting, Generalized Linear Models, AdaOpt with nnetsauce and mlsauce Dec 29, 2020. New activation functions in mlsauce's LSBoost Feb 12, 2021. An infinity of time series models in nnetsauce Mar 6, 2021. Explaining xgboost predictions with the teller Mar 12, 2021. Compatibility of nnetsauce and mlsauce with scikit-learn Mar 26, 2021. Bayesian Optimization with GPopt Apr 16, 2021. Bayesian Optimization with GPopt Part 2 (save and resume) Apr 30, 2021. A forecasting tool (API) with examples in curl, R, Python May 28, 2021. Hyperparameters tuning with GPopt Jun 11, 2021. How to use linear regression forecast indicator code#
Documentation and source code for GPopt, a package for Bayesian optimization Jul 2, 2021.
How to use linear regression forecast indicator plus#
`crossvalidation` on R-universe, plus a classification example Jul 23, 2021. parallel grid search cross-validation using `crossvalidation` Jul 31, 2021. `crossvalidation` and random search for calibrating support vector machines Aug 6, 2021. Classification using linear regression Sep 26, 2021. Automatic Forecasting with `ahead::dynrmf` and Ridge regression Oct 22, 2021. Fast and scalable forecasting with ahead::ridge2f Oct 31, 2021. Time series cross-validation using `crossvalidation` (Part 2) Nov 7, 2021. Tuning and interpreting LSBoost Nov 15, 2021. How to use linear regression forecast indicator install#
However, you can install nnetsauce from GitHub as follows: Let \(K \in \mathbb_k(x)\]Ĭurrently, installing nnetsauce from Pypi doesn’t work – and I’m working on fixing it. Model descriptionĬhapter 4 of Elements of Statistical Learning (ESL), at section 4.2 Linear Regression of an Indicator Matrix, describes classification using linear regression pretty well. In addition, the source code is relatively self-explanatory. If you’re not interested in reading about the model description, you can jump directly to the 2nd section, “Two examples in Python”. In this post, I illustrate classification using linear regression, as implemented in Python/R package nnetsauce, and more precisely, in nnetsauce’s MultitaskClassifier.
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