ValueError: could not convert string to float while implementing sklearn
1
I am new in this, I am getting some error like this ;
File "C:UsersHimanshuDesktopProjectMLPractmlp1.py", line 268, in
<module> cv_results = model_selection.cross_val_score(model, X_train, Y_train,
cv=kfold, scoring=scoring)
File "C:UsersHimanshuAppDataRoamingPythonPython27site-
packagessklearnmodel_selection_validation.py", line 402, in cross_val_score
error_score=error_score)
.
.
etc..like above)
ValueError: could not convert string to float: transact
the shape of the dataset I am using is (30,216)
array = dataset.values
X = array[:,0:215]
Y = array[:,215]
validation_size = 0.20
seed = 7
X_train, X_validation, Y_train, Y_validation =
model_selection.train_test_split(X, Y, test_size=validation_size,
random_state=seed)
I want to know, am I Splitting it correctly or not.
Can someone please suggest why this error is occurring.
Edited:
I am adding the rest of the code :
scoring = 'accuracy'
# Spot Check Algorithms
models =
models.append(('LR', LogisticRegression()))
models.append(('LDA', LinearDiscriminantAnalysis()))
models.append(('KNN', KNeighborsClassifier()))
models.append(('CART', DecisionTreeClassifier()))
models.append(('NB', GaussianNB()))
models.append(('SVM', SVC()))
# evaluate each model in turn
results =
names =
for name, model in models:
kfold = model_selection.KFold(n_splits=10, random_state=seed)
cv_results = model_selection.cross_val_score(model, X_train, Y_train,
cv=kfold, scoring=scoring)
results.append(cv_results)
names.append(name)
msg = "%s: %f (%f)" % (name, cv_results.mean(), cv_results.std())
print(msg)
python python-2.7 machine-learning scikit-learn sklearn-pandas
asked Nov 25 '18 at 19:37
Ashwani TandonAshwani Tandon
62
add a comment |
1
I am new in this, I am getting some error like this ;
File "C:UsersHimanshuDesktopProjectMLPractmlp1.py", line 268, in
<module> cv_results = model_selection.cross_val_score(model, X_train, Y_train,
cv=kfold, scoring=scoring)
File "C:UsersHimanshuAppDataRoamingPythonPython27site-
packagessklearnmodel_selection_validation.py", line 402, in cross_val_score
error_score=error_score)
.
.
etc..like above)
ValueError: could not convert string to float: transact
the shape of the dataset I am using is (30,216)
array = dataset.values
X = array[:,0:215]
Y = array[:,215]
validation_size = 0.20
seed = 7
X_train, X_validation, Y_train, Y_validation =
model_selection.train_test_split(X, Y, test_size=validation_size,
random_state=seed)
I want to know, am I Splitting it correctly or not.
Can someone please suggest why this error is occurring.
Edited:
I am adding the rest of the code :
scoring = 'accuracy'
# Spot Check Algorithms
models =
models.append(('LR', LogisticRegression()))
models.append(('LDA', LinearDiscriminantAnalysis()))
models.append(('KNN', KNeighborsClassifier()))
models.append(('CART', DecisionTreeClassifier()))
models.append(('NB', GaussianNB()))
models.append(('SVM', SVC()))
# evaluate each model in turn
results =
names =
for name, model in models:
kfold = model_selection.KFold(n_splits=10, random_state=seed)
cv_results = model_selection.cross_val_score(model, X_train, Y_train,
cv=kfold, scoring=scoring)
results.append(cv_results)
names.append(name)
msg = "%s: %f (%f)" % (name, cv_results.mean(), cv_results.std())
print(msg)
python python-2.7 machine-learning scikit-learn sklearn-pandas
asked Nov 25 '18 at 19:37
Ashwani TandonAshwani Tandon
62
1
You have some string values in your dataX_train. Convert them to numbers
– Vivek Kumar
Nov 26 '18 at 7:44
add a comment |
1
1
1
1
I am new in this, I am getting some error like this ;
File "C:UsersHimanshuDesktopProjectMLPractmlp1.py", line 268, in
<module> cv_results = model_selection.cross_val_score(model, X_train, Y_train,
cv=kfold, scoring=scoring)
File "C:UsersHimanshuAppDataRoamingPythonPython27site-
packagessklearnmodel_selection_validation.py", line 402, in cross_val_score
error_score=error_score)
.
.
etc..like above)
ValueError: could not convert string to float: transact
the shape of the dataset I am using is (30,216)
array = dataset.values
X = array[:,0:215]
Y = array[:,215]
validation_size = 0.20
seed = 7
X_train, X_validation, Y_train, Y_validation =
model_selection.train_test_split(X, Y, test_size=validation_size,
random_state=seed)
I want to know, am I Splitting it correctly or not.
Can someone please suggest why this error is occurring.
Edited:
I am adding the rest of the code :
scoring = 'accuracy'
# Spot Check Algorithms
models =
models.append(('LR', LogisticRegression()))
models.append(('LDA', LinearDiscriminantAnalysis()))
models.append(('KNN', KNeighborsClassifier()))
models.append(('CART', DecisionTreeClassifier()))
models.append(('NB', GaussianNB()))
models.append(('SVM', SVC()))
# evaluate each model in turn
results =
names =
for name, model in models:
kfold = model_selection.KFold(n_splits=10, random_state=seed)
cv_results = model_selection.cross_val_score(model, X_train, Y_train,
cv=kfold, scoring=scoring)
results.append(cv_results)
names.append(name)
msg = "%s: %f (%f)" % (name, cv_results.mean(), cv_results.std())
print(msg)
python python-2.7 machine-learning scikit-learn sklearn-pandas
asked Nov 25 '18 at 19:37
Ashwani TandonAshwani Tandon
62
I am new in this, I am getting some error like this ;
File "C:UsersHimanshuDesktopProjectMLPractmlp1.py", line 268, in
<module> cv_results = model_selection.cross_val_score(model, X_train, Y_train,
cv=kfold, scoring=scoring)
File "C:UsersHimanshuAppDataRoamingPythonPython27site-
packagessklearnmodel_selection_validation.py", line 402, in cross_val_score
error_score=error_score)
.
.
etc..like above)
ValueError: could not convert string to float: transact
the shape of the dataset I am using is (30,216)
array = dataset.values
X = array[:,0:215]
Y = array[:,215]
validation_size = 0.20
seed = 7
X_train, X_validation, Y_train, Y_validation =
model_selection.train_test_split(X, Y, test_size=validation_size,
random_state=seed)
I want to know, am I Splitting it correctly or not.
Can someone please suggest why this error is occurring.
Edited:
I am adding the rest of the code :
scoring = 'accuracy'
# Spot Check Algorithms
models =
models.append(('LR', LogisticRegression()))
models.append(('LDA', LinearDiscriminantAnalysis()))
models.append(('KNN', KNeighborsClassifier()))
models.append(('CART', DecisionTreeClassifier()))
models.append(('NB', GaussianNB()))
models.append(('SVM', SVC()))
# evaluate each model in turn
results =
names =
for name, model in models:
kfold = model_selection.KFold(n_splits=10, random_state=seed)
cv_results = model_selection.cross_val_score(model, X_train, Y_train,
cv=kfold, scoring=scoring)
results.append(cv_results)
names.append(name)
msg = "%s: %f (%f)" % (name, cv_results.mean(), cv_results.std())
print(msg)
python python-2.7 machine-learning scikit-learn sklearn-pandas
python python-2.7 machine-learning scikit-learn sklearn-pandas
asked Nov 25 '18 at 19:37
Ashwani TandonAshwani Tandon
62
asked Nov 25 '18 at 19:37
Ashwani TandonAshwani Tandon
62
edited Nov 25 '18 at 21:22
Ashwani Tandon
asked Nov 25 '18 at 19:37
Ashwani TandonAshwani Tandon
62
asked Nov 25 '18 at 19:37
Ashwani TandonAshwani Tandon
62
asked Nov 25 '18 at 19:37
Ashwani TandonAshwani Tandon
62
62
1
You have some string values in your dataX_train. Convert them to numbers
– Vivek Kumar
Nov 26 '18 at 7:44
add a comment |
1
You have some string values in your dataX_train. Convert them to numbers
– Vivek Kumar
Nov 26 '18 at 7:44
1
1
You have some string values in your data
X_train. Convert them to numbers– Vivek Kumar
Nov 26 '18 at 7:44
You have some string values in your data
X_train. Convert them to numbers– Vivek Kumar
Nov 26 '18 at 7:44
add a comment |
0
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1
You have some string values in your data
X_train. Convert them to numbers– Vivek Kumar
Nov 26 '18 at 7:44