Accuracy of the model Unicorn Meta Zoo #1: Why another podcast? Announcing the arrival of Valued Associate #679: Cesar Manara 2019 Moderator Election Q&A - Questionnaire 2019 Community Moderator Election ResultsCheck Accuracy of Model Provided by ConsultantHow to calculate accuracy on keras model with multiple outputs?Accuracy improvement for logistic regression modelMax 75% accuracy! help!Coursera ML - Does the choice of optimization algorithm affect the accuracy of multiclass logistic regression?Tensorflow regression predicting 1 for all inputsThe validation loss < training loss and validation accuracy < training accuracyWhat is the classification accuracy of a random classifier?My accuracy changes throughout every epoc but the val_acc at the end of each epoc stays the sameHow do data scientists test the claimed accuracy of a model?
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Accuracy of the model
Unicorn Meta Zoo #1: Why another podcast?
Announcing the arrival of Valued Associate #679: Cesar Manara
2019 Moderator Election Q&A - Questionnaire
2019 Community Moderator Election ResultsCheck Accuracy of Model Provided by ConsultantHow to calculate accuracy on keras model with multiple outputs?Accuracy improvement for logistic regression modelMax 75% accuracy! help!Coursera ML - Does the choice of optimization algorithm affect the accuracy of multiclass logistic regression?Tensorflow regression predicting 1 for all inputsThe validation loss < training loss and validation accuracy < training accuracyWhat is the classification accuracy of a random classifier?My accuracy changes throughout every epoc but the val_acc at the end of each epoc stays the sameHow do data scientists test the claimed accuracy of a model?
$begingroup$
I'm using this dataset and i'm trying to do logistic regression
heart_data = pd.read_csv('../input/heart-disease-uci/heart.csv')
X = heart_data.iloc[:,:-1]
y = heart_data.iloc[:,-1]
X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.20,random_state=5,shuffle=True)
from sklearn.preprocessing import MinMaxScaler
nr = MinMaxScaler()
X_train = nr.fit_transform(X_train)
X_test = nr.transform(X_test)
from sklearn.metrics import accuracy_score,confusion_matrix
def cal(method,c=1):
lr = LogisticRegression(C=c,solver=method)
for i in method:
print(i,'->>>>>>>>',cal(i))
First is training accuracy and second one is testing accuracy.
why am i getting more testing accuracy over training?
And Is there another way to increase the both accuracy?
I'm using min-max scaling so are there any other normalization to increase the accuracy more or this is the best accuracy we can get using logistic?
machine-learning feature-selection logistic-regression accuracy
edited 2 hours ago
oW_♦
3,496933
asked 2 hours ago
Utsav PatelUtsav Patel
1
New contributor
Utsav Patel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I'm using this dataset and i'm trying to do logistic regression
heart_data = pd.read_csv('../input/heart-disease-uci/heart.csv')
X = heart_data.iloc[:,:-1]
y = heart_data.iloc[:,-1]
X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.20,random_state=5,shuffle=True)
from sklearn.preprocessing import MinMaxScaler
nr = MinMaxScaler()
X_train = nr.fit_transform(X_train)
X_test = nr.transform(X_test)
from sklearn.metrics import accuracy_score,confusion_matrix
def cal(method,c=1):
lr = LogisticRegression(C=c,solver=method)
for i in method:
print(i,'->>>>>>>>',cal(i))
First is training accuracy and second one is testing accuracy.
why am i getting more testing accuracy over training?
And Is there another way to increase the both accuracy?
I'm using min-max scaling so are there any other normalization to increase the accuracy more or this is the best accuracy we can get using logistic?
machine-learning feature-selection logistic-regression accuracy
edited 2 hours ago
oW_♦
3,496933
asked 2 hours ago
Utsav PatelUtsav Patel
1
New contributor
Utsav Patel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I'm using this dataset and i'm trying to do logistic regression
heart_data = pd.read_csv('../input/heart-disease-uci/heart.csv')
X = heart_data.iloc[:,:-1]
y = heart_data.iloc[:,-1]
X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.20,random_state=5,shuffle=True)
from sklearn.preprocessing import MinMaxScaler
nr = MinMaxScaler()
X_train = nr.fit_transform(X_train)
X_test = nr.transform(X_test)
from sklearn.metrics import accuracy_score,confusion_matrix
def cal(method,c=1):
lr = LogisticRegression(C=c,solver=method)
for i in method:
print(i,'->>>>>>>>',cal(i))
First is training accuracy and second one is testing accuracy.
why am i getting more testing accuracy over training?
And Is there another way to increase the both accuracy?
I'm using min-max scaling so are there any other normalization to increase the accuracy more or this is the best accuracy we can get using logistic?
machine-learning feature-selection logistic-regression accuracy
edited 2 hours ago
oW_♦
3,496933
asked 2 hours ago
Utsav PatelUtsav Patel
1
New contributor
Utsav Patel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I'm using this dataset and i'm trying to do logistic regression
heart_data = pd.read_csv('../input/heart-disease-uci/heart.csv')
X = heart_data.iloc[:,:-1]
y = heart_data.iloc[:,-1]
X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.20,random_state=5,shuffle=True)
from sklearn.preprocessing import MinMaxScaler
nr = MinMaxScaler()
X_train = nr.fit_transform(X_train)
X_test = nr.transform(X_test)
from sklearn.metrics import accuracy_score,confusion_matrix
def cal(method,c=1):
lr = LogisticRegression(C=c,solver=method)
for i in method:
print(i,'->>>>>>>>',cal(i))
First is training accuracy and second one is testing accuracy.
why am i getting more testing accuracy over training?
And Is there another way to increase the both accuracy?
I'm using min-max scaling so are there any other normalization to increase the accuracy more or this is the best accuracy we can get using logistic?
machine-learning feature-selection logistic-regression accuracy
machine-learning feature-selection logistic-regression accuracy
edited 2 hours ago
oW_♦
3,496933
asked 2 hours ago
Utsav PatelUtsav Patel
1
New contributor
Utsav Patel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 2 hours ago
oW_♦
3,496933
asked 2 hours ago
Utsav PatelUtsav Patel
1
New contributor
Utsav Patel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 2 hours ago
oW_♦
3,496933
edited 2 hours ago
oW_♦
3,496933
edited 2 hours ago
oW_♦
3,496933
3,496933
asked 2 hours ago
Utsav PatelUtsav Patel
1
New contributor
Utsav Patel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 hours ago
Utsav PatelUtsav Patel
1
asked 2 hours ago
Utsav PatelUtsav Patel
1
1
New contributor
Utsav Patel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Utsav Patel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Utsav Patel is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
add a comment |
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