Update tutorials #35
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Update tutorials #35
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ml-evs
reviewed
Mar 5, 2021
| @@ -155,6 +156,7 @@ def get_cross_nmi(df_feat: pd.DataFrame, **kwargs) -> pd.DataFrame: | |||
| )[0] / (0.5 * (diag[x_feat] + diag[y_feat])) | |||
| mutual_info.loc[y_feat, x_feat] = mutual_info.loc[x_feat, y_feat] = I_xy | |||
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| mutual_info.fillna(0, inplace=True) # if na => no relation => set to zero | |||
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Just commenting on this as something we should discuss in a moment
Co-authored-by: Matthew Evans <[email protected]>
Co-authored-by: Matthew Evans <[email protected]>
Co-authored-by: Matthew Evans <[email protected]>
ml-evs
requested changes
Mar 9, 2021
modnet/preprocessing.py
Outdated
| @@ -157,7 +158,7 @@ def get_cross_nmi(df_feat: pd.DataFrame, **kwargs) -> pd.DataFrame: | |||
| mutual_info.loc[y_feat, x_feat] = mutual_info.loc[x_feat, y_feat] = I_xy | |||
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| mutual_info.fillna(0, inplace=True) # if na => no relation => set to zero | |||
| return mutual_info | |||
| return mutual_info, diag # diag can be useful for future elimination based on entropy without the need of recomputing the cross NMI | |||
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Could we just set the diagonal values in the dataframe instead of setting them to 1, so we don't need to return this? This change breaks the existing API otherwise
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Example notebooks updates to v0.1.9
Plus a few accompanying inner updates (each has its corresponding commit).
materialsargument, but conservingstructuresargument for backward compatibilityChemEnvSiteFingerprint|GaussianSymmFuncmean G2_0.05should beGaussianSymmFunc|mean G2_0.05(as used in MP_2018.6 on figshare)