Machine Learning (Regression and Classification) demo
This demo is used in MATLAB EXPO 2016 at Tokyo.
There are one non-machine learning and three machine learning examples.
0. Data Analysis - Olympic medal analysis (non-machine learning)
1. Regression - House Price Estimation in Osaka
- linear model
- stepwise regression
- Gaussian Process Regression
2. Classification - New York Taxi Tip Estimation
- Preprocessing with categorical and summary function
- Classification Learner Apps
- Bayesian Optimization
3. BigDataProcessing
- simple tall array & linear regression examples
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MATLAB EXPO 2016 の C3 データの本質を読み解くための機械学習 セッションで使用したコードです。
機械学習ではない例が1つ、機械学習の例が3つ含まれています。
0. Data Analysis - オリンピックメダル解析 (機械学習ではない例)
1. Regression - 大阪の住宅価格予測モデルの構築
- 線形モデル
- ステップワイズ回帰
- ガウス過程回帰
2. Classification - New York のタクシーチップの推定
- categorical や summary 関数を使った前処理
- 分類学習器アプリ
- ベイズ最適化
3. BigDataProcessing
- tall 配列と線形回帰を組み合わせた例
こちらの内容を紹介したビデオ:
https://jp.mathworks.com/videos/machine-learning-for-understanding-data-tackling-data-analytics-issues-with-matlab-123658.html
Cite As
mizuki (2024). Machine Learning (Regression and Classification) demo (https://www.mathworks.com/matlabcentral/fileexchange/59844-machine-learning-regression-and-classification-demo), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform Compatibility
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- AI and Statistics > Statistics and Machine Learning Toolbox > Regression > Model Building and Assessment > Bayesian Regression >
- AI and Statistics > Statistics and Machine Learning Toolbox > Analysis of Big Data with Tall Arrays >
Tags
Acknowledgements
Inspired by: READHGT: Import/download NASA SRTM data files (.HGT)
Inspired: Raman Finder
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