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Python 2022-02-18 10:00:14
python linear regression
# import the class from sklearn.linear_model import LogisticRegression # instantiate the model (using the default parameters) logreg = LogisticRegression() # fit the model with data logreg.fit(X_train,y_train) # y_pred=logreg.predict(X_test) Add solution -
Python 2022-02-18 07:30:05
multiclass classification model
knn=KNeighborsClassifier() svc=SVC() lr=LogisticRegression() dt=DecisionTreeClassifier() gnb=GaussianNB() rfc=RandomForestClassifier() xgb=XGBClassifier() gbc=GradientBoostingClassifier() ada=AdaBoostClassifier() ------------------------------------------... Add solution -
Python 2021-10-27 18:39:11
word embeddings sklearn
from sklearn.linear_model import LogisticRegresion from zeugma.embeddings import EmbeddingTransformer glove = EmbeddingTransformer('glove') x_train = glove.transform(corpus_train) model = LogisticRegression() model.fit(x_train, y_train) x_test = glove.... Add solution -
Python 2021-10-07 19:29:04
word embedding
from sklearn.linear_model import LogisticRegresion from zeugma.embeddings import EmbeddingTransformer glove = EmbeddingTransformer('glove') x_train = glove.transform(corpus_train) model = LogisticRegression() model.fit(x_train, y_train) x_test = glove.... Add solution