2. JUDUL PROPOSAL
Pengkajian Kemampuan Algoritma
Maximum Likelihood, Support
Vector Machine dan Fuzzy Logic
dalam Memetakan Lamun menggunakan
Citra Multi-Skala
6. Maximum Likelihood
The name of the function is log_lik.
The function tpdf (which is part of the
Statistics toolbox) computes the probability
density function of a Standard Student's t
distribution.
tpdf(data,n) returns a vector of densities
(one density for each observation in the
vector data), under the hypothesis that the
number of degrees of freedom is equal to n.
7. Support Vector Machine
X — Matrix of predictor data, where each row is one
observation, and each column is one predictor.
Y — Array of class labels with each row corresponding to the
value of the corresponding row in X.
KernelFunction — The default value is 'linear' for two-class
learning, which separates the data by a hyperplane.
Standardize — Flag indicating whether the software should
standardize the predictors before training the classifier.
ClassNames — Distinguishes between the negative and positive
classes, or specifies which classes to include in the data.
The negative class is the first element (or row of a character
array), e.g., 'negClass', and the positive class is the second
element (or row of a character array),
e.g., 'posClass'. ClassNames must be the same data type as Y.
