Python package of machine learning for imbalanced data #machine_learning #chemoinformatics

Recently I’m struggling with imbalanced data. I didn’t have any idea to handle it. So my predictive model showed poor performance. Some days ago, I found useful package for imbalanced data learning which name is ‘imbalanced learn‘. It can be installed from conda. The package provides methods for over sampling and under sampling. I hadContinue reading “Python package of machine learning for imbalanced data #machine_learning #chemoinformatics”

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Vote Vote Vote #chemoinformatics

Somedays ago, I posted about ensemble classification method named ‘blending’. The method is not implemented in scikit-learn. So I am implementing the function now. By the way, scikit-learn has an ensemble classification method named ‘VotingClassifer’. https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingClassifier.html#sklearn.ensemble.VotingClassifier Following explanation from sklearn document. The idea behind the VotingClassifier is to combine conceptually different machine learning classifiers andContinue reading “Vote Vote Vote #chemoinformatics”

Visualize important features of machine leaning #RDKit

As you know, rdkit2018 09 01 has very exiting method named ‘DrawMorganBit’ and ‘DrawMorganBits’. It can render the bit information of fingerprint. It is described the following blog post. http://rdkit.blogspot.com/2018/10/using-new-fingerprint-bit-rendering-code.html And if you can read Japanese, Excellent posts are provided. View at Medium.com https://future-chem.com/rdkit-fp-visualize/ What I want to do in the blog post is thatContinue reading “Visualize important features of machine leaning #RDKit”