from mit_d3m import load_dataset
dataset = load_dataset('LL0_uci_yacht_hydrodynamics')
X = dataset.X
y = dataset.y
context = dataset.context
0.4710803525816578
featuretools.dfs
sklearn.preprocessing.Imputer
sklearn.preprocessing.StandardScaler
xgboost.XGBRegressor
featuretools.dfs#1
"encode": true
"max_depth": 3
"remove_low_information": true
sklearn.preprocessing.Imputer#1
"missing_values": NaN
"axis": 0
"copy": true
"strategy": median
sklearn.preprocessing.StandardScaler#1
"with_mean": false
"with_std": false
xgboost.XGBRegressor#1
"n_jobs": -1
"n_estimators": 451
"max_depth": 3
"learning_rate": 0.2606511673396348
"gamma": 0.0004898635069590096
"min_child_weight": 5
| ColIndex | ColName | ColType | Role |
|---|