Cpp ML Library: Class Members

Cpp ML Library 1.0.0

A library of Machine Learning Algorithmns seen from the Udemy course Machine Learning A to Z.

Here is a list of all documented class members with links to the class documentation for each member:

- a -

Apriori() : Apriori

- b -

backProp() : NeuralNetwork

- c -

calcHiddenGradients() : Neuron
calcOutputGradients() : Neuron

- d -

DecisionTreeClassifier() : DecisionTreeClassifier
DecisionTreeRegressor() : DecisionTreeRegressor
deltaWeight : Connection

- e -

Eclat() : Eclat

- f -

feedForward() : NeuralNetwork , Neuron
fit() : DecisionTreeClassifier , DecisionTreeRegressor , HierarchicalClustering , KMeans , KNNClassifier , KNNRegressor , RandomForestClassifier , RandomForestRegressor , SupportVectorRegression

- g -

get_cluster_centers() : HierarchicalClustering , KMeans
get_support_counts() : Apriori , Eclat
getBias() : MultilinearRegression
getCoefficients() : PolynomialRegression
getOutputVal() : Neuron
getRecentAverageError() : NeuralNetwork
getResults() : NeuralNetwork
getWeights() : MultilinearRegression

- h -

HierarchicalClustering() : HierarchicalClustering

- i -

itemset_to_string() : Apriori

- k -

KernelType : SupportVectorRegression
KMeans() : KMeans
KNNClassifier() : KNNClassifier
KNNRegressor() : KNNRegressor

- l -

Linkage : HierarchicalClustering
LogisticRegression() : LogisticRegression

- m -

MultilinearRegression() : MultilinearRegression

- n -

NeuralNetwork() : NeuralNetwork
Neuron() : Neuron

- p -

PolynomialRegression() : PolynomialRegression
predict() : DecisionTreeClassifier , DecisionTreeRegressor , HierarchicalClustering , KMeans , KNNClassifier , KNNRegressor , LogisticRegression , MultilinearRegression , PolynomialRegression , RandomForestClassifier , RandomForestRegressor , SupportVectorRegression
predictProbability() : LogisticRegression

- r -

RandomForestClassifier() : RandomForestClassifier
RandomForestRegressor() : RandomForestRegressor
run() : Apriori , Eclat

- s -

setOutputVal() : Neuron
SupportVectorRegression() : SupportVectorRegression

- t -

train() : LogisticRegression , MultilinearRegression , PolynomialRegression

- u -

updateInputWeights() : Neuron

- w -

weight : Connection

- ~ -

~DecisionTreeClassifier() : DecisionTreeClassifier
~DecisionTreeRegressor() : DecisionTreeRegressor
~HierarchicalClustering() : HierarchicalClustering
~KMeans() : KMeans
~KNNClassifier() : KNNClassifier
~KNNRegressor() : KNNRegressor
~RandomForestClassifier() : RandomForestClassifier
~RandomForestRegressor() : RandomForestRegressor
~SupportVectorRegression() : SupportVectorRegression