Unit 1
Statistical decision making techniques: Bayes’ theorem – Multiple features – Conditionally independent features – Decision boundaries – Unequal costs of error – Estimation of error rates – Leaving one out technique – Characteristic curves.
| Course Name | Pattern Recognition Techniques and Algorithms |
| Course Code | 15ECE331 |
| Program | B. Tech. in Electronics and Communication Engineering |
| Year Taught | 2019 |
Statistical decision making techniques: Bayes’ theorem – Multiple features – Conditionally independent features – Decision boundaries – Unequal costs of error – Estimation of error rates – Leaving one out technique – Characteristic curves.
Non-parametric decision making techniques: Histograms – Kernel and window estimators – Nearest neighbor classification techniques – Adaptive decision boundaries – Adaptive discriminant functions – Minimum squared error discriminant functions – Choosing a decision making technique.
Artificial neural networks: nets without hidden layers – Nets with hidden layers – Back propagation algorithm – Hopfield nets.
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