Data centric Explainable ML Tutorial 11: Lab 4 Step 4

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In step 3, we observed relatively high training and test model accuracy and an improved land cover map. In this step, we will use explainable machine learning techniques to gain insights into the model performance.

Additional resources
Data-centric Explainable Machine Learning for Land Cover Classification: A Practical Guide in R

Explanatory Model Analysis: Explore, Explain, and Examine Predictive Models. With examples in R and Python.

R Script for Lab 4

Lab 4 Data Set (Download Links)

Courage Kamusoko

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Hello dear the main objective of feature selection or reduction is to improve model accuracy…for me I was tested a pca but the accuracy is not increase so I decided to tuning the model am using hyperparameter tunning is that possible thank you for the reply

saidokieh

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