Sklearn Vorhersage python3.5

Question

Ich trainiere ein logistisches Regressionsmodell mit sklearn LogisticRegression. Ich erhalte einen TypeError, wenn ich versuche, den Testsatz vorherzusagen.

Code:

test_features=test[["Sex","Age","Pclass","Fare","Embarked"]].values 
myprediction=myfit2.predict(test_features) 

ERROR:

float() argument must be a string or a number

ich die Syntax ein paar times.Could dies sein geprüft habe, weil ich mit Python bin 3.5. Weil dies auf Python 2.7 gut zu funktionieren scheint. Würde mich sehr über Hilfe freuen, um diesen Fehler zu beheben.

Answer 1

Das Problem ist, dass die Daten enthalten NaN:

Code:

import pandas as pd 
from numpy import nanmean 
import numpy as np 
from sklearn.linear_model import LogisticRegression 

train = pd.read_csv("train.csv") 
test = pd.read_csv("test.csv") 

test["Sex"][test["Sex"]=="male"]=0 
test["Sex"][test["Sex"]=="female"]=1 
test["Embarked"][test["Embarked"]=='S']=0 
test["Embarked"][test["Embarked"]=='C']=1 
test["Embarked"][test["Embarked"]=='Q']=2 

train["Sex"][train["Sex"]=="male"]=0 
train["Sex"][train["Sex"]=="female"]=1 
train["Embarked"][train["Embarked"]=='S']=0 
train["Embarked"][train["Embarked"]=='C']=1 
train["Embarked"][train["Embarked"]=='Q']=2 

nan_mean_age = nanmean(test.iloc[:,4]) 
test = test.fillna(value = nan_mean_age) 

nan_mean_age2 = nanmean(train.iloc[:,5]) 
train = train.fillna(value = nan_mean_age2) 

train_features=train[["Sex","Age","Pclass","Fare","Embarked"]].values 
test_features=test[["Sex","Age","Pclass","Fare","Embarked"]].values 

train_features = np.asarray(train_features) 
test_features = np.asarray(test_features) 

lg = LogisticRegression() 
#define your target variable y and then fit 
y_train = train.iloc[:,1] 

lg.fit(train_features,y_train) 
lg.predict(test_features) 

Ergebnis:

array([0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 
     1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 
     0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 
     1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 
     1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 
     0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 
     1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 
     0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 
     1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 
     0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 
     0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 
     0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 
     0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 
     0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 
     0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 
     1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 
     1, 0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 
     1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 
     1, 0, 0, 0], dtype=int64) 

So etwas sollte gut funktionieren