Instructions to use Bluepearl/Random-Forest-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bluepearl/Random-Forest-Classification with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Bluepearl/Random-Forest-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 510 Bytes
47d08e5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | from sklearn import preprocessing
class FuncToNumber:
def ToNumber(df):
# transform non-numerical labels to numerical labels
#Name,Sex,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked
le = preprocessing.LabelEncoder()
df["Sex"] = le.fit_transform(df["Sex"])
df["Age"] = le.fit_transform(df["Age"])
df["Ticket"] = le.fit_transform(df["Ticket"])
df["Fare"] = le.fit_transform(df["Fare"])
df["Cabin"] = le.fit_transform(df["Cabin"])
return df |