Scikit Learn : Confusion Matrix, Accuracy, Precision and Recall




[ad_1]

Scikit Learn : Confusion Matrix, Accuracy, Precision and Recall

Source


[ad_2]

Comment List

  • Dragonfly Statistics
    November 23, 2020

    Very bad audio

  • Dragonfly Statistics
    November 23, 2020

    THANK YOU SO MUCH!!!!!!!

  • Dragonfly Statistics
    November 23, 2020

    not working for more than 2 classes

  • Dragonfly Statistics
    November 23, 2020

    Nice video sir , what does support infer in the precision, recall table

  • Dragonfly Statistics
    November 23, 2020

    Is it possible to use TensorFlow to predict the model /object feature which concerns about measurement thanks in advance…

  • Dragonfly Statistics
    November 23, 2020

    Nice…share jupyter notebook

  • Dragonfly Statistics
    November 23, 2020

    thank you loads!

  • Dragonfly Statistics
    November 23, 2020

    Great video. Could you help: How can I assign the accuracy to a variable, like a=accuracy or a = binary_accuracy. This is part of the code of the neural network:

    model = Sequential()

    model.add(Dense(48, input_dim=48, activation='relu'))

    model.add(Dense(24, activation='relu'))

    model.add(Dense(2, activation='sigmoid'))

    model.compile(loss='mean_squared_error',

    optimizer='adam',

    metrics=['binary_accuracy']

    model.fit(training_data, target_data, epochs=1000)

    scores = model.evaluate(training_data, target_data)

    "training_data, target_data are arrays"

    Result of evaluation:

    binary_accuracy: 0.5000

    binary_accuracy: 50.00%

  • Dragonfly Statistics
    November 23, 2020

    Hi,
    How can I explain to some accuracy score to someone.
    I mean if it 95%,how I can explain it and wht is it indicating?
    Please explain it

  • Dragonfly Statistics
    November 23, 2020

    not audible.Cannot hear your voice

  • Dragonfly Statistics
    November 23, 2020

    why the avg/total is 93 in precision

  • Dragonfly Statistics
    November 23, 2020

    I think 347 should be the false positive and 263 should be the false negative. correct me if I'm wrong.

  • Dragonfly Statistics
    November 23, 2020

    hi, I'm having this error:
    ValueError: Classification metrics can't handle a mix of multiclass and continuous targets
    any idea how to rectify it?

  • Dragonfly Statistics
    November 23, 2020

    Very helpfull!!

  • Dragonfly Statistics
    November 23, 2020

    how to reduce the model score value
    i am getting it as 1.0 for my dataset
    how can i reduce it?

  • Dragonfly Statistics
    November 23, 2020

    in classification report i got all the values as zeroes for class 0 and some values for class 1(precision,recall,f1) how do i correct this

  • Dragonfly Statistics
    November 23, 2020

    i have a [[0,34],[0,61]] in confusion matrix how do i interpret this as? and if its wrong how do i correct this

  • Dragonfly Statistics
    November 23, 2020

    great video lad

  • Dragonfly Statistics
    November 23, 2020

    Very nicely explained thank you sir!

  • Dragonfly Statistics
    November 23, 2020

    hey bro! do you want 10000 viewers from my country? contact me if interested at my email ms9678204@gmail.com

Write a comment