(The Gist of Science Reporter) How the Machine Learns

[August-2020]

How the Machine Learns

• “The dataset in our work is like a matrix with each row represented by material, and each column represents a specific feature of the material,” explains Arnab Kabiraj, first author of the study. Their dataset contained 157 materials, each with 1500 properties. “We then employed a 3-part method of processing,” he elaborates:
• Select Percentile – the dataset columns are reduced by selecting the best features and discarding the irrelevant ones.
• Zero Counts – all zero-valued data generated after step 1 are eliminated at this stage. And finally, the data is subjected to a standard supervised Machine Learning technique.
• Gradient Boosting Regressor – an ensemble-based model that uses a predictor – like a decision tree – to enhance performance.

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Courtesy: Science Reporter