Creative Commons
CrowdFlower
pip install mit-d3m
2.7 MB
from mit_d3m import load_dataset
dataset = load_dataset('twitter-hate-speech-classifier-DFE-a845520')
X = dataset.X
y = dataset.y
context = dataset.context
0.7187006875703721
mlprimitives.preprocessing.ClassEncoder
mlprimitives.feature_extraction.StringVectorizer
sklearn.preprocessing.Imputer
sklearn.ensemble.RandomForestClassifier
mlprimitives.preprocessing.ClassDecoder
mlprimitives.preprocessing.ClassEncoder#1
mlprimitives.feature_extraction.StringVectorizer#1
"features": auto
"input": content
"decode_error": ignore
"analyzer": word
"lowercase": true
"binary": true
"max_features": 292
sklearn.preprocessing.Imputer#1
"missing_values": NaN
"axis": 0
"copy": true
"strategy": mean
sklearn.ensemble.RandomForestClassifier#1
"n_jobs": -1
"criterion": gini
"max_features":
"max_depth": 18
"min_samples_split": 0.007991137807668223
"min_samples_leaf": 0.003517175006875175
"n_estimators": 345
"class_weight": balanced
mlprimitives.preprocessing.ClassDecoder#1
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