Im using GridSearchCV to find the best parameters for my model OneClassSVM.
I have read in documentation that nu value should be between 0 and 1.
In my code, I always get error :
ValueError: nu <= 0 or nu > 1
What am I doing wrong?
import pandas as pd
from sklearn.svm import OneClassSVM
from sklearn.model_selection import GridSearchCV
import numpy as np
df = pd.read_csv('pitanja.csv')
#print(df)
x = df.iloc[:,:-1]
tuned_svm = {'cache_size':[70,80,90], 'coef0':[0.25,0.5,0.75], 'gamma':['auto'],
'kernel':['poly','rbf','linear','sigmoid', 'precomputed'], 'random_state':[None],
'shrinking':[True,False], 'tol':[0.05,0.1,0.2], 'verbose':[True],
'nu':[0.1, 0.11, 0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.19, 0.2, 0.21, 0.22, 0.23, 0.24,0,25,0.26,0.27]}
def scorer_f(estimator, X): #your own scorer
return np.mean(estimator.score_samples(X))
out_cls = GridSearchCV(OneClassSVM(), tuned_svm, scorer_f)
r = df
model = out_cls .fit(x)
prediction = model.predict(x)
print(model.best_params_)
Spotted the error:
'nu':[0.1, 0.11, 0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.19, 0.2, 0.21, 0.22, 0.23, 0.24,0,25,0.26,0.27]
If you are tired of manually typing in these values, I recommend to use 'nu':[0.1, np.linspace(0.11,0.27,17)].