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January 2017

27

Jan'17

203.6.9 SVM : Conclusion

SVM Advantages & Disadvantages SVM Advantages In previous section, we studied about  Digit Recognition using SVM SVM’s are very good …

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27

Jan'17

203.6.8 Digit Recognition using SVM

LAB: Digit Recognition using SVM In previous section, we studied about Soft Margin Classification – Noisy Data and Validation Take …

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27

Jan'17

203.6.7 Soft Margin Classification – Noisy Data and Validation

Soft Margin Classification – Noisy data In previous section, we studied about Kernel – Non Linear Classifier Noisy data What …

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27

Jan'17

203.6.6 Practice : Kernel – Non Linear Classifier

In previous section, we studied about  The Non-Linear Decision Boundary In this session we will practice non linear kernels of …

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27

Jan'17

203.6.5 The Non-Linear Decision Boundary

The Non-Linear Decision Boundary In previous section, we studied about Building SVM model in R In the above examples we …

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27

Jan'17

203.6.4 Building SVM model in R

We discussed the SVM algorithm in our last post. In this post we will try to build a SVM classification …

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