from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score
import pandas as pd
df = pd.read_csv("result.csv")
x_train = df.drop(columns=['status','device_id'])[:6]
y_train = df['status'][:6]
x_test = df.drop(columns=['status','device_id'])[6:]
y_test = df['status'][6:]
model = RandomForestClassifier(
n_estimators=100,random_state=42,
)
model.fit(x_train,y_train)
prediction = model.predict(x_test)
print(prediction)
accuracy = accuracy_score(y_test, prediction)
print(accuracy)