Trending Technology Machine Learning, Artificial Intelligent, Block Chain, IoT, DevOps, Data Science

Recent Post

Codecademy Code Foundations

Search This Blog

Evaluation and Cross-Validation

Experimental Evaluation of Learning Algorithms :-

Evaluating the performance of learning systems is important because :
  - Learning systems are usually designed to predict the class of "future" unlabeled data points.
Typical choices for performance Evaluation
  - Error 
  - Accuracy
  - Precision/Recall
Typical choices for Sampling Methods :
  - Train/Test Sets
  - K-Fold Cross-validation

Evaluating predictions

Suppose we want to make a prediction of a value for a target feature on example x :
  - y is the observed value of target feature on example x.
  - Ŷ is the predicted value of target feature on example x.
  - How is the error measured?

Sample Error and True Error

The sample error of hypothesis f with respect to target function c and data sample S is :
       errors(f) = 1/n ⅀xεsD (f(x),C(x))
The true error (denoted error (f)) of  hypothesis f with respect to target function c and distribution D, is the probability that h will misclassify an instance drawn at random according to D.
          errors(f) = Pr xεD(f(x)≠C(x))

Difficulties in evaluating hypotheses with limited data

Bias in the estimate : The sample error is a poor estimate of true error
  - ==> test the hypothesis on an independent test set 
We divide the example into:
  - Training examples that are used to train the learner
  - Test examples that are used to evaluate the learner
Variance in the estimate : The smaller the test set, the greater the expected variance.

Validation Set



K-fold cross validation





Trade-off

In machine learning, there is always a trade-off between
  - complex hypotheses that fit the training data well
  - simpler hypotheses that may generalize better.
As the amount of training data increases, the generalization error decreases.

4 comments:

  1. nice information on data science has given thank you very much.
    Data Science coaching in Hyderabad

    ReplyDelete
  2. nice information on data science has given thank you very much.
    Data Science coaching in Hyderabad

    ReplyDelete
  3. your article on data science is very good keep it up thank you for sharing.
    Data Science coaching in Hyderabad

    ReplyDelete
  4. When looking at the trusted reviews from their Google Checkout, it was concluded that they had a 4.5 star rating, with the website showing the good reviews and bad complaints altogether. Safer Reviews

    ReplyDelete

John Academy