Remove Data Collection Remove Data mining Remove Knowledge Discovery Remove Machine Learning
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Fundamentals of Data Mining

Data Science 101

This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Machine learning provides the technical basis for data mining.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

Machine Learning algorithms often need to handle highly-imbalanced datasets. This in turns makes the performance evaluation of the classifier difficult, and can also harm the learning of an algorithm that strives to maximise accuracy. A weighted nearest neighbor algorithm for learning with symbolic features. Quinlan, J.

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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Conference on Knowledge Discovery and Data Mining, pp.

Modeling 139