fake-new-lstm's Introduction
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iamsantoshkumar saravanapriyand nishant5790 filippomariglia sourabhsd jagadishchaudari mps24-7uk subhamio asadkhanek electrotechnik amenouni kharishanker kirtiwardhan01 suneelkumar999 vipulsatyendra varungowdaa tusharkalecam vishalgardas jitendramishra1024 projectifyofficial sanyamjain789523 adarsh666 ritu-lalwani vivekpython-art rajajrds tarun-yadav777 anandshakya-cyber farman8962 satyamkumar073 raghusenapati ingledarshan white-peed deesaw istiyak97 themrityunjay abdelrhman-gaber ravisahu2017 ash1909 sonalighadage hasnaetalibi mayukhm devil55555 rimanshu s-modi rgpihlstrom zlszhonglongshen novik1 amandeepsingh1111 garvitmodi malinisn satyajitmohapatra-datascientist chuka19952 wahab1983 sourav3365 m-nosrati vidulakamat awathesuyash ramgitrepo suryaaseran ovinduwijethunge susvicky maheshmechengg ssiva18 rohithye2001 dashrath1260 dhinagaran-s saurabh-0077 augustolozano vinay-art jesuissusnata satsin727 iamrosan divyamsingh18 avr8 karthikfrd17 puneethreddy nafisahmad kaushik95mr pranayghosh18 sridhark12 iamshalabh shashibhoi manikandaprabhu01 rohan-1907 avisheak yagya-buttan windblaze1 arnavism mahin493 tahabi09 zqcsrz junyms karmathecoder abdelkadergelany shivcode21 neda60 rajat-dhanuka sanketbairagi riddhiman-ghatak sarthak-vishnufake-new-lstm's Issues
predict_classes
y_pred=model.predict_classes(X_test)
then i use predict only instead of predict classes
but accuracy and matrix shows an error
then i use argmax after predict it gives less accuracy
how to get 90+accuracy??
y_pred = model1.predict(x_test)
y_pred[1]
class_x=np.argmax(y_pred,axis=1)
class_x
array([0, 0, 0, ..., 0, 0, 0])
from sklearn.metrics import accuracy_score, confusion_matrix
score = accuracy_score(y_test, class_x)
score
0.5578342904019689
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