andy
1513f2b378
Affected files: STEM/AI/Classification/Classification.md STEM/AI/Classification/Decision Trees.md STEM/AI/Classification/Gradient Boosting Machine.md STEM/AI/Classification/Logistic Regression.md STEM/AI/Classification/Random Forest.md STEM/AI/Classification/Supervised.md STEM/AI/Classification/Supervised/README.md STEM/AI/Classification/Supervised/SVM.md STEM/AI/Classification/Supervised/Supervised.md STEM/AI/Learning.md STEM/AI/Neural Networks/Learning/Boltzmann.md STEM/AI/Neural Networks/Learning/Competitive Learning.md STEM/AI/Neural Networks/Learning/Credit-Assignment Problem.md STEM/AI/Neural Networks/Learning/Hebbian.md STEM/AI/Neural Networks/Learning/Learning.md STEM/AI/Neural Networks/Learning/README.md STEM/AI/Neural Networks/RNN/Autoencoder.md STEM/AI/Neural Networks/RNN/Deep Image Prior.md STEM/AI/Neural Networks/RNN/MoCo.md STEM/AI/Neural Networks/RNN/Representation Learning.md STEM/AI/Neural Networks/RNN/SimCLR.md STEM/img/comp-learning.png STEM/img/competitive-geometric.png STEM/img/confusion-matrix.png STEM/img/decision-tree.png STEM/img/deep-image-prior-arch.png STEM/img/deep-image-prior-results.png STEM/img/hebb-learning.png STEM/img/moco.png STEM/img/receiver-operator-curve.png STEM/img/reinforcement-learning.png STEM/img/rnn+autoencoder-variational.png STEM/img/rnn+autoencoder.png STEM/img/simclr.png STEM/img/sup-representation-learning.png STEM/img/svm-c.png STEM/img/svm-non-linear-project.png STEM/img/svm-non-linear-separated.png STEM/img/svm-non-linear.png STEM/img/svm-optimal-plane.png STEM/img/svm.png STEM/img/unsup-representation-learning.png |
||
|---|---|---|
| .. | ||
| README.md | ||
| Supervised.md | ||
| SVM.md | ||
Gaussian Classifier
- With
Tlabelled data
q_t(i)=
\begin{cases}
1 & \text{if class } i \\
0 & \text{otherwise}
\end{cases}$$
- Indicator function
- Mean parameter
$$\hat m_i=\frac{\sum_tq_t(i)o_t}{\sum_tq_t(i)}$$
- Variance parameter
$$\hat v_i=\frac{\sum_tq_t(i)(o_t-\hat m_i)^2}{\sum_tq_t(i)}$$
- Distribution weight
- Class prior
- $P(N_i)$
$$\hat c_i=\frac 1 T \sum_tq_t(i)$$
$$\hat \mu_i=\frac{\sum_{t=1}^Tq_t(i)o_t}{\sum_{t=1}^Tq_t(i)}$$
$$\hat\sum_i=\frac{\sum_{t=1}^Tq_t(i)(o_t-\mu_i)(o_t-\mu_i)^T}{\sum_{t=1}^Tq_t(i)}$$
- For K-dimensional