From bd6b24ec15df52b737395f3e53bae4b51fc0b9f4 Mon Sep 17 00:00:00 2001 From: github-actions <${GITHUB_ACTOR}@users.noreply.github.com> Date: Mon, 22 Jun 2020 11:54:53 +0000 Subject: [PATCH] Documentation for 98b2609e1bcc51799717a6fc500c1c6fee148173 --- annotated.html | 2 +- classes.html | 2 +- d0/d01/smallest__circle_8cpp.html | 2 +- d0/d08/realtime__stats_8cpp.html | 2 +- d0/d0d/structmst-members.html | 2 +- d0/d55/classcll-members.html | 2 +- ...tatistics_1_1stats__computer1-members.html | 2 +- .../number__of__positive__divisors_8cpp.html | 2 +- d0/db6/non__recursive__merge__sort_8cpp.html | 2 +- d0/dc4/struct_point-members.html | 2 +- d0/dd2/class_queue___array.html | 2 +- d0/de2/gaussian__elimination_8cpp.html | 2 +- d0/dff/structlinkedlist.html | 2 +- d1/d07/class_solution-members.html | 2 +- d1/d11/gcd__of__n__numbers_8cpp.html | 2 +- d1/d1d/class_graph-members.html | 2 +- d1/d21/quick__sort_8cpp.html | 2 +- d1/d76/buzz__number_8cpp.html | 2 +- d1/d77/structmst.html | 2 +- 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namespacemembers_func.html | 2 +- namespaces.html | 2 +- pages.html | 2 +- search/all_5.js | 2 +- search/defines_2.js | 3 +- search/defines_3.js | 2 +- search/defines_4.js | 4 +- search/defines_5.js | 8 +- search/defines_6.js | 4 +- search/groups_0.js | 2 +- search/groups_1.js | 2 +- search/groups_2.js | 2 +- search/pages_0.js | 2 +- search/pages_1.js | 2 +- search/pages_2.js | 2 +- search/pages_3.js | 4 +- 270 files changed, 1317 insertions(+), 1299 deletions(-) diff --git a/annotated.html b/annotated.html index 2bfefd3e7..31a2561f8 100644 --- a/annotated.html +++ b/annotated.html @@ -141,7 +141,7 @@ $(document).ready(function(){initNavTree('annotated.html',''); initResizable();
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1.8.18 Kohonen self organizing map (topological map)
-This example implements a powerful unsupervised learning algorithm called as a self organizing map. The algorithm creates a connected network of weights that closely follows the given data points. This thus creates a topological map of the given data i.e., it maintains the relationship between varipus data points in a much higher dimesional space by creating an equivalent in a 2-dimensional space.
Main function
-w11.csv: initial random mapw12.csv: trained SOM map w21.csv: initial random mapw22.csv: trained SOM map w31.csv: initial random mapw32.csv: trained SOM map
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1.8.18 Adaptive Linear Neuron (ADALINE) implementation
source ADALINE is one of the first and simplest single layer artificial neural network. The algorithm essentially implements a linear function
+
+ADALINE is one of the first and simplest single layer artificial neural network. The algorithm essentially implements a linear function
\[ f\left(x_0,x_1,x_2,\ldots\right) = \sum_j x_jw_j+\theta \]
where \(x_j\) are the input features of a sample, \(w_j\) are the coefficients of the linear function and \(\theta\) is a constant. If we know the \(w_j\), then for any given set of features, \(y\) can be computed. Computing the \(w_j\) is a supervised learning algorithm wherein a set of features and their corresponding outputs are given and weights are computed using stochastic gradient descent method.
@@ -179,27 +180,27 @@ FunctionsMain function
-
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1.8.18 true size matches false size does not match Operator to print the weights of the model
-
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1.8.18 Linear regression example using Ordinary least squares
-Program that gets the number of data samples and number of features per sample along with output per sample. It applies OLS regression to compute the regression output for additional test data samples.
+Get matrix inverse using Row-trasnformations. Given matrix must be a square and non-singular.
matrix transpose
function to check if given matrix is a square matrix
main function
-pre-multiplication of a vector by a scalar
Matrix multiplication such that if A is size (mxn) and B is of size (pxq) then the multiplication is defined only when n = p and the resultant matrix is of size (mxq)
multiplication of a matrix with a column vector
post-multiplication of a vector by a scalar
addition of two vectors of identical lengths
subtraction of two vectors of identical lengths
operator to print a matrix
-operator to print a vector
-
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1.8.18 define \(f(x)\) to find root for
-define \(f(x)\) to find root for. Currently defined as:
+\[ f(x) = x^3 - 4x - 9 \] +
+define the derivative function \(f'(x)\)
-define the derivative function \(f'(x)\) For the current problem, it is:
+\[ f'(x) = 3x^2 - 4 \] +
+Main function
-
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