GitHub - inshatazeen/Machine-learning-Rocks-Categorisation: This is a real-world rock dataset that compiles more than 1700 magmatic rocks in southern Peru and northern Chile. These data samples document compositional variations of magmas since Jurassic time with a focus on the Neogene period, when major crustal thickening developed and its influence on magma composition was most pronounced. The dataset has 1788 rock samples (i.e. rows) and 101 descriptive features (i.e. columns) in total, and many have missing values. About the classification task: The task is to use machine learning algorithms to automatically categorize samples into several types -- ash, lava, ignimbrite, etc. In the data file, it corresponds to the "Sample

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This is a real-world rock dataset that compiles more than 1700 magmatic rocks in southern Peru and northern Chile. These data samples document compositional variations of magmas since Jurassic time with a focus on the Neogene period, when major crustal thickening developed and its influence on magma composition was most pronounced. The dataset h…

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