Pertanyaan yang diberi tag xgboost

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Kapan harus memilih regresi linier atau Pohon Keputusan atau regresi Hutan Acak? [Tutup]

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machine-learning algorithms random-forest linear-regression decision-trees machine-learning predictive-modeling forecast r clustering similarity data-mining dataset statistics text-mining text-mining data-cleaning data-wrangling machine-learning classification algorithms xgboost data-mining dataset dataset regression graphs svm unbalanced-classes cross-validation optimization hyperparameter genetic-algorithms visualization predictive-modeling correlation machine-learning predictive-modeling apache-spark statistics normalization apache-spark map-reduce r correlation confusion-matrix r data-cleaning classification terminology dataset image-classification machine-learning regression apache-spark machine-learning data-mining nlp parsing machine-learning dimensionality-reduction visualization clustering multiclass-classification evaluation unsupervised-learning machine-learning machine-learning data-mining supervised-learning unsupervised-learning machine-learning data-mining classification statistics predictive-modeling data-mining clustering python pandas machine-learning dataset data-cleaning data bigdata software-recommendation
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Output Regresi Linier XGBo salah

Saya seorang pemula untuk XGBoost, jadi maafkan ketidaktahuan saya. Berikut adalah kode python: import pandas as pd import xgboost as xgb df = pd.DataFrame({'x':[1,2,3], 'y':[10,20,30]}) X_train = df.drop('y',axis=1) Y_train = df['y'] T_train_xgb = xgb.DMatrix(X_train, Y_train) params =...

python linear-regression xgboost