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”
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”
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”
Some days ago, I wanted data that was scaled. I found scikit-learn is best practice. Like this…. Then, I got…. It was easy !