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Method in class <A HREF="./AlgorithmKMeans.html" title="class in <Unnamed>">AlgorithmKMeans</A><DD>Computes the means of the data sets after each iteraion<DT><A HREF="./MathUtil.html#computeMyPointMean(java.util.Vector)"><B>computeMyPointMean(Vector)</B></A> - Static method in class <A HREF="./MathUtil.html" title="class in <Unnamed>">MathUtil</A><DD>methods computes and returns the mean of the given cluster<DT><A HREF="./MathUtil.html#computePointMean(java.util.Vector)"><B>computePointMean(Vector)</B></A> - Static method in class <A HREF="./MathUtil.html" title="class in <Unnamed>">MathUtil</A><DD>methods computes and returns the mean of the given cluster<DT><A HREF="./AlgorithmRVM.html#computeSigma()"><B>computeSigma()</B></A> - Method in class <A HREF="./AlgorithmRVM.html" title="class in <Unnamed>">AlgorithmRVM</A><DD>Computes the sigma valued defined on pp.<DT><A HREF="./AlgorithmSVM.html#computeSupportVectors()"><B>computeSupportVectors()</B></A> - Method in class <A HREF="./AlgorithmSVM.html" title="class in <Unnamed>">AlgorithmSVM</A><DD>method computes the all the support vectors<DT><A HREF="./AlgorithmRVM.html#computeVarianceCholesky()"><B>computeVarianceCholesky()</B></A> - Method in class <A HREF="./AlgorithmRVM.html" title="class in <Unnamed>">AlgorithmRVM</A><DD>Computes the diagonal elements of the inverse from the cholesky decomposition<DT><A HREF="./DataPoints.html#convertMyPoint(MyPoint, int, int, DisplayScale)"><B>convertMyPoint(MyPoint, int, int, DisplayScale)</B></A> - Static method in class <A HREF="./DataPoints.html" title="class in <Unnamed>">DataPoints</A><DD>Converts an instance of MyPoint to an instance of Point<DT><A HREF="./DataPoints.html#convertMyPoints(java.util.Vector, int, int, DisplayScale)"><B>convertMyPoints(Vector<MyPoint>, int, int, DisplayScale)</B></A> - Static method in class <A HREF="./DataPoints.html" title="class in <Unnamed>">DataPoints</A><DD>Converts a Vector of MyPoints to a Vector of points that correspond to Java coordinates.<DT><A HREF="./DataPoints.html#convertPoint(java.awt.Point, int, int, DisplayScale)"><B>convertPoint(Point, int, int, DisplayScale)</B></A> - Static method in class <A HREF="./DataPoints.html" title="class in <Unnamed>">DataPoints</A><DD>Converts an instance of Point to an instance of MyPoint containing the cartesian x-y values<DT><A HREF="./DataPoints.html#convertPoints(java.util.Vector, int, int, DisplayScale)"><B>convertPoints(Vector<Point>, int, int, DisplayScale)</B></A> - Static method in class <A HREF="./DataPoints.html" title="class in <Unnamed>">DataPoints</A><DD>Converts a vector of Points to a vector of MyPoints containing the cartesian x-y values<DT><A HREF="./DecisionRegion.html#copy()"><B>copy()</B></A> - Method in class <A HREF="./DecisionRegion.html" title="class in <Unnamed>">DecisionRegion</A><DD> <DT><A HREF="./OutputPanel.html#copy()"><B>copy()</B></A> - Method in class <A HREF="./OutputPanel.html" title="class in <Unnamed>">OutputPanel</A><DD>Duplicates the OutputPanel Object<DT><A HREF="./Matrix.html#copyLowerMatrix(Matrix)"><B>copyLowerMatrix(Matrix)</B></A> - Method in class <A HREF="./Matrix.html" title="class in <Unnamed>">Matrix</A><DD>this routine computes the inverse of a matrix<DT><A HREF="./Matrix.html#copyMatrix(Matrix)"><B>copyMatrix(Matrix)</B></A> - Method in class <A HREF="./Matrix.html" title="class in <Unnamed>">Matrix</A><DD>This routine takes a matrix as an argument and copies it to the the matrix object that invoked it<DT><A HREF="./Matrix.html#copyMatrixRows(Matrix, boolean[])"><B>copyMatrixRows(Matrix, boolean[])</B></A> - Method in class <A HREF="./Matrix.html" title="class in <Unnamed>">Matrix</A><DD>This routine takes a matrix as an argument and copies its rows to the the matrix object that invoked it only for columns that the flags are true.<DT><A HREF="./MathUtil.html#copyVector(java.util.Vector, java.util.Vector, int, int, int)"><B>copyVector(Vector<Double>, Vector<Double>, int, int, int)</B></A> - Static method in class <A HREF="./MathUtil.html" title="class in <Unnamed>">MathUtil</A><DD>Copies vector given specific parameters<DT><A HREF="./Covariance.html" title="class in <Unnamed>"><B>Covariance</B></A> - Class in <A HREF="./package-summary.html"><Unnamed></A><DD>Covariance as the name sggests computes the covariance matrix given two random vectors i.e., the X = (x1, x2, x3 ...) and Y = (y1, y2, y3 ...)<DT><A HREF="./Covariance.html#Covariance()"><B>Covariance()</B></A> - Constructor for class <A HREF="./Covariance.html" title="class in <Unnamed>">Covariance</A><DD> </DL><HR><A NAME="_D_"><!-- --></A><H2><B>D</B></H2><DL><DT><A HREF="./DataPoints.html" title="class in <Unnamed>"><B>DataPoints</B></A> - Class in <A HREF="./package-summary.html"><Unnamed></A><DD>class holds the input DataPoints classes that are to be classified as well as the classification algorithms needed to compute the decision regions<DT><A HREF="./DecisionRegion.html" title="class in <Unnamed>"><B>DecisionRegion</B></A> - Class in <A HREF="./package-summary.html"><Unnamed></A><DD>class: DecisionRegion class that stores the point of the various decision regions computed<DT><A HREF="./DecisionRegion.html#decisionRegion"><B>decisionRegion</B></A> - Variable in class <A HREF="./DecisionRegion.html" title="class in <Unnamed>">DecisionRegion</A><DD> <DT><A HREF="./Matrix.html#decompositionCholesky(Matrix)"><B>decompositionCholesky(Matrix)</B></A> - Method in class <A HREF="./Matrix.html" title="class in <Unnamed>">Matrix</A><DD>this method constructs the Cholesky decomposition of an input matrix: W.<DT><A HREF="./Classify.html#DetermineDimensions()"><B>DetermineDimensions()</B></A> - Method in class <A HREF="./Classify.html" title="class in <Unnamed>">Classify</A><DD>determines the dimensions of the selection area<DT><A HREF="./DisplayArea.html#DetermineDimensions()"><B>DetermineDimensions()</B></A> - Method in class <A HREF="./DisplayArea.html" title="class in <Unnamed>">DisplayArea</A><DD>determine the dimensions of the selection area<DT><A HREF="./SelectionArea.html#DetermineDimensions()"><B>DetermineDimensions()</B></A> - Method in class <A HREF="./SelectionArea.html" title="class in <Unnamed>">SelectionArea</A><DD>Determines the dimensions of the selection area<DT><A HREF="./Matrix.html#DIAGONAL"><B>DIAGONAL</B></A> - Static variable in class <A HREF="./Matrix.html" title="class in <Unnamed>">Matrix</A><DD> <DT><A HREF="./Algorithm.html#disableControl()"><B>disableControl()</B></A> - Method in class <A HREF="./Algorithm.html" title="class in <Unnamed>">Algorithm</A><DD>Disables the next and previous keys before beggining to execute a step.<DT><A HREF="./AlgorithmLP.html#display_result(double[], double[], double[], double, double, int, int)"><B>display_result(double[], double[], double[], double, double, int, int)</B></A> - Method in class <A HREF="./AlgorithmLP.html" title="class in <Unnamed>">AlgorithmLP</A><DD>Display the results in the process box<DT><A HREF="./DisplayArea.html" title="class in <Unnamed>"><B>DisplayArea</B></A> - Class in <A HREF="./package-summary.html"><Unnamed></A><DD>class implements the graph plot that displays the output points and the comouted decision region based on the algorithm used<DT><A HREF="./DisplayArea.html#DisplayArea()"><B>DisplayArea()</B></A> - Constructor for class <A HREF="./DisplayArea.html" title="class in <Unnamed>">DisplayArea</A><DD>constructor initializes the samples to be plotted in the signal panel<DT><A HREF="./AlgorithmKMeans.html#displayClusterError(int, java.util.Vector, int)"><B>displayClusterError(int, Vector, int)</B></A> - Method in class <A HREF="./AlgorithmKMeans.html" title="class in <Unnamed>">AlgorithmKMeans</A><DD>determines the number of points in error, i.e, not classified by finding the distance of the datapoints from the closest of the vector set<DT><A HREF="./AlgorithmLBG.html#displayClusterError(int, java.util.Vector, int)"><B>displayClusterError(int, Vector, int)</B></A> - Method in class <A HREF="./AlgorithmLBG.html" title="class in <Unnamed>">AlgorithmLBG</A><DD>Finds the datapoints in error, for all datasets<DT><A HREF="./AlgorithmLDA.html#displayMatrices()"><B>displayMatrices()</B></A> - Method in class <A HREF="./AlgorithmLDA.html" title="class in <Unnamed>">AlgorithmLDA</A><DD>Display two matrices - covariance matrix and the transformation matrix in the text message window<DT><A HREF="./AlgorithmLDAPCA.html#displayMatrices()"><B>displayMatrices()</B></A> - Method in class <A HREF="./AlgorithmLDAPCA.html" title="class in <Unnamed>">AlgorithmLDAPCA</A><DD>Display two matrices - covariance matrix and the transformation matrix in the text message window<DT><A HREF="./MathUtil.html#distance(double, double, double, double)"><B>distance(double, double, double, double)</B></A> - Static method in class <A HREF="./MathUtil.html" title="class in <Unnamed>">MathUtil</A><DD>calculate the euclidean distance between the two points<DT><A HREF="./MathUtil.html#doubleValue(java.util.Vector, int)"><B>doubleValue(Vector<Double>, int)</B></A> - Static method in class <A HREF="./MathUtil.html" title="class in <Unnamed>">MathUtil</A><DD>gets the double value of the input vector at the index passed<DT><A HREF="./AlgorithmPF.html#drawGaussian(double, double, int)"><B>drawGaussian(double, double, int)</B></A> - Method in class <A HREF="./AlgorithmPF.html" title="class in <Unnamed>">AlgorithmPF</A><DD>Draws Gaussian points around each data point<DT><A HREF="./DataPoints.html#drawGaussian(double, double, DisplayScale)"><B>drawGaussian(double, double, DisplayScale)</B></A> - Method in class <A HREF="./DataPoints.html" title="class in <Unnamed>">DataPoints</A><DD>Draws Gaussian distribution by calling setGaussian()<DT><A HREF="./DisplayArea.html#DrawGrid(java.awt.Graphics)"><B>DrawGrid(Graphics)</B></A> - Method in class <A HREF="./DisplayArea.html" title="class in <Unnamed>">DisplayArea</A><DD>draw the selection area grid lines<DT><A HREF="./SelectionArea.html#DrawGrid(java.awt.Graphics)"><B>DrawGrid(Graphics)</B></A> - Method in class <A HREF="./SelectionArea.html" title="class in <Unnamed>">SelectionArea</A><DD>Draws the selection area grid lines<DT><A HREF="./Classify.html#drawPoint(java.awt.Graphics, java.awt.Point, int, java.awt.Color)"><B>drawPoint(Graphics, Point, int, Color)</B></A> - Static method in class <A HREF="./Classify.html" title="class in <Unnamed>">Classify</A><DD>determine the dimensions of the selection area actually this draws a line of width 3 pixels in either directions in way, this draws a + sign..<DT><A HREF="./Classify.html#drawPoints(java.awt.Graphics, java.util.Vector, int, java.awt.Color)"><B>drawPoints(Graphics, Vector, int, Color)</B></A> - Static method in class <A HREF="./Classify.html" title="class in <Unnamed>">Classify</A><DD>determine the dimensions of the selection area</DL><HR><A NAME="_E_"><!-- --></A><H2><B>E</B></H2><DL><DT><A HREF="./Matrix.html#Elem"><B>Elem</B></A> - Variable in class <A HREF="./Matrix.html" title="class in <Unnamed>">Matrix</A><DD> <DT><A HREF="./Algorithm.html#enableControl()"><B>enableControl()</B></A> - Method in class <A HREF="./Algorithm.html" title="class in <Unnamed>">Algorithm</A><DD>Enables the next and previous keys after the execution of a step.<DT><A HREF="./AlgorithmLP.html#estimate(java.util.Vector, java.util.Vector, double, double[])"><B>estimate(Vector<MyPoint>, Vector<MyPoint>, double, double[])</B></A> - Method in class <A HREF="./AlgorithmLP.html" title="class in <Unnamed>">AlgorithmLP</A><DD>Estimates the amplitude based on the LP coeficients.<DT><A HREF="./Matrix.html#expMatrix()"><B>expMatrix()</B></A> - Method in class <A HREF="./Matrix.html" title="class in <Unnamed>">Matrix</A><DD>This routine takes every element to its exponent with Math.exp()</DL><HR><A NAME="_F_"><!-- --></A><H2><B>F</B></H2><DL><DT><A HREF="./AlgorithmLP.html#final_estimate()"><B>final_estimate()</B></A> - Method in class <A HREF="./AlgorithmLP.html" title="class in <Unnamed>">AlgorithmLP</A><DD>Calculates the estimated points for the data inputs<DT><A HREF="./Matrix.html#FULL"><B>FULL</B></A> - Static variable in class <A HREF="./Matrix.html" title="class in <Unnamed>">Matrix</A><DD> </DL><HR><A NAME="_G_"><!-- --></A><H2><B>G</B></H2><DL><DT><A HREF="./BiNormal.html#gaussian(int, double, double, double[], double[], double, double, double, double)"><B>gaussian(int, double, double, double[], double[], double, double, double, double)</B></A> - Method in class <A HREF="./BiNormal.html" title="class in <Unnamed>">BiNormal</A><DD>Generates binormal gaussian random deviates<DT><A HREF="./Matrix.html#gaussj(double[][], int, double[][], int)"><B>gaussj(double[][], int, double[][], int)</B></A> - Method in class <A HREF="./Matrix.html" title="class in <Unnamed>">Matrix</A><DD>This routine computes the inverse matrix using the gauss jordan method see numerical recipes, the are of scientific computing, second edition, cambridge university press.<DT><A HREF="./AlgorithmKMeans.html#generateMeans(int)"><B>generateMeans(int)</B></A> - Method in class <A HREF="./AlgorithmKMeans.html" title="class in <Unnamed>">AlgorithmKMeans</A><DD>Generates random initial guesses (means) for the data set⌨️ 快捷键说明
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