title: How to increase true positive in your classification Machine Learning model?
body: <p>I am new to Machine Learning
  I have a dataset which has highly unbalanced classes(dominated by negative class) and contains more than 2K numeric features and the target is [0,1]. I have trained a logistics regression though I am getting an accuracy of 89% but from confusion matrix, it was found the model True positive is very low. Below are the scores of my model</p>
  <p><code>Accuracy Score : 0.8965989500114129</code></p>
  <p><code>Precision Score : 0.3333333333333333</code></p>
  <p><code>Recall Score : 0.029545454545454545</code></p>
  <p><code>F1 Score : 0.05427974947807933</code></p>
  <p>How I can increase my True Positives? Should I be using a different classification model?</p>
  <p>I have tried the PCA and represented my data in 2 components, it increased the model accuracy up to 90%(approx) however True Positives was decreased again</p>