Contents
Gaussian Naïve Bayes.............................................................................................................................1
Random Forest.......................................................................................................................................2
logistic Regression..................................................................................................................................3
Ensemble................................................................................................................................................4
Linear regression....................................................................................................................................5
Plotting...................................................................................................................................................7
NLP.........................................................................................................................................................9
ANN.....................................................................................................................................................12
CNN......................................................................................................................................................16
Python Introduction/ Pandas................................................................................................................21
Gaussian Naïve Bayes
!! alle waarden moeten reële getallen zijn
Bv. Male female omzetten naar 0 en 1
Maak train en test sets aan
o Survived moet je vervangen door de kolom die je wil bekijken
Bereken de accuracy
Bepaal rappel en precisie (false negative rate)
1
,Random Forest
N_estimators = aantal bomen
Belangrijkheid per klasse weergeven
2
, # we now combine those two collections into a dataframe
pd.DataFrame(model.feature_importances_,columns=['Importance'],index=X_train.columns).sort_va
lues(by='Importance',ascending=False)
logistic Regression
3
Gaussian Naïve Bayes.............................................................................................................................1
Random Forest.......................................................................................................................................2
logistic Regression..................................................................................................................................3
Ensemble................................................................................................................................................4
Linear regression....................................................................................................................................5
Plotting...................................................................................................................................................7
NLP.........................................................................................................................................................9
ANN.....................................................................................................................................................12
CNN......................................................................................................................................................16
Python Introduction/ Pandas................................................................................................................21
Gaussian Naïve Bayes
!! alle waarden moeten reële getallen zijn
Bv. Male female omzetten naar 0 en 1
Maak train en test sets aan
o Survived moet je vervangen door de kolom die je wil bekijken
Bereken de accuracy
Bepaal rappel en precisie (false negative rate)
1
,Random Forest
N_estimators = aantal bomen
Belangrijkheid per klasse weergeven
2
, # we now combine those two collections into a dataframe
pd.DataFrame(model.feature_importances_,columns=['Importance'],index=X_train.columns).sort_va
lues(by='Importance',ascending=False)
logistic Regression
3
