\\( +b_x \\) is the positive the probability increases that the student will pass the exam. \\(-b_x\\) is the negative the probability decreases that the student will pass the exam.
\\( +b_x \\) is the positive the probability increases that the student will pass the exam. \\(-b_x\\) is the negative the probability decreases that the student will pass the exam.
In addition you can take a look at the odds ratio. The odds ratio describes the change in the ratio of the probability.
In addition you can take a look at the odds ratio. The odds ratio describes the change in the ratio of the probability.
## Training the network
## Training the model
Logistic regression is a supervised learning algorithm. The training data is used to train the network. The network is trained by minimizing the error function. The error function or accuracy is the difference between the predicted and the actual value. The error function or accuracy function is used to measure the quality of the network.
Logistic regression is a supervised learning algorithm. The training data is used to train the network. The network is trained by minimizing the error function. The error function or accuracy is the difference between the predicted and the actual value. The error function or accuracy function is used to measure the quality of the network.
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@@ -57,4 +57,4 @@ If you want to learn more about logistic regression, checkout the scikit-learn [
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@@ -57,4 +57,4 @@ If you want to learn more about logistic regression, checkout the scikit-learn [
