Creative Commons
Crowdflower
pip install mit-d3m
3.0 MB
from mit_d3m import load_dataset
dataset = load_dataset('twitter-airline-sentiment')
X = dataset.X
y = dataset.y
context = dataset.context
0.906591569865326
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": 322
sklearn.preprocessing.Imputer#1
"missing_values": NaN
"axis": 0
"copy": true
"strategy": most_frequent
sklearn.ensemble.RandomForestClassifier#1
"n_jobs": -1
"criterion": entropy
"max_features":
"max_depth": 15
"min_samples_split": 0.11994304901323953
"min_samples_leaf": 0.00449098322860945
"n_estimators": 221
"class_weight":
mlprimitives.preprocessing.ClassDecoder#1
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