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Add Logistic Regression
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@KevinCoble
KevinCoble committed May 20, 2016
1 parent 3b8ef12 commit 2f005d1
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Showing 11 changed files with 562 additions and 57 deletions.
12 changes: 12 additions & 0 deletions AIToolbox.xcodeproj/project.pbxproj
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Expand Up @@ -49,6 +49,10 @@
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Expand Down Expand Up @@ -144,6 +148,8 @@
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Expand Down Expand Up @@ -305,6 +311,7 @@
0E02FB921CBDD35300C32F9F /* MixtureOfGaussians.swift */,
0E02FB981CC1B22E00C32F9F /* NonLinearRegression.swift */,
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0E3CB5AA1CE6C9FB008ABA4E /* LogisticRegression.swift */,
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);
path = AIToolbox;
Expand Down Expand Up @@ -337,6 +344,7 @@
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);
path = AIToolboxTests;
Expand Down Expand Up @@ -560,6 +568,7 @@
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Expand Down Expand Up @@ -597,6 +606,7 @@
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Expand All @@ -619,6 +629,7 @@
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Expand Down Expand Up @@ -649,6 +660,7 @@
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77 changes: 77 additions & 0 deletions AIToolbox/DataSet.swift
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Original file line number Diff line number Diff line change
Expand Up @@ -118,6 +118,7 @@ public class DataSet {
}
}

/// Get entries from another matching dataset
public func includeEntries(fromDataSet fromDataSet: DataSet, withEntries: [Int]) throws
{
// Make sure the dataset matches
Expand All @@ -142,6 +143,7 @@ public class DataSet {
}
}

/// Get entries from another matching dataset
public func includeEntries(fromDataSet fromDataSet: DataSet, withEntries: ArraySlice<Int>) throws
{
// Make sure the dataset matches
Expand All @@ -166,6 +168,46 @@ public class DataSet {
}
}

/// Get inputs from another matching dataset, initializing outputs to 0
public func includeEntryInputs(fromDataSet fromDataSet: DataSet, withEntries: [Int]) throws
{
// Make sure the dataset inputs match
if inputDimension != fromDataSet.inputDimension { throw DataTypeError.WrongDimensionOnInput }

// Copy the inputs
for index in withEntries {
if (index < 0) { throw DataIndexError.Negative }
if (index >= fromDataSet.size) { throw DataIndexError.IndexAboveDataSetSize }
inputs.append(fromDataSet.inputs[index])
if (dataType == .Regression) {
outputs!.append([Double](count:outputDimension, repeatedValue: 0.0))
}
else {
classes!.append(0)
}
}
}

/// Get inputs from another matching dataset, initializing outputs to 0
public func includeEntryInputs(fromDataSet fromDataSet: DataSet, withEntries: ArraySlice<Int>) throws
{
// Make sure the dataset inputs match
if inputDimension != fromDataSet.inputDimension { throw DataTypeError.WrongDimensionOnInput }

// Copy the inputs
for index in withEntries {
if (index < 0) { throw DataIndexError.Negative }
if (index >= fromDataSet.size) { throw DataIndexError.IndexAboveDataSetSize }
inputs.append(fromDataSet.inputs[index])
if (dataType == .Regression) {
outputs!.append([Double](count:outputDimension, repeatedValue: 0.0))
}
else {
classes!.append(0)
}
}
}

public var size: Int
{
return inputs.count
Expand Down Expand Up @@ -333,6 +375,41 @@ public class DataSet {
return results
}

public func groupClasses() throws
{
if (dataType != .Classification) { throw DataTypeError.InvalidDataType }

// If the data already has classification data, skip
if (optionalData != nil) {
if optionalData is ClassificationData { return }
}

// Create a classification data addendum
let classificationData = ClassificationData()

// Get the different data labels
for index in 0..<size {
let thisClass = classes![index]
let thisClassIndex = classificationData.foundLabels.indexOf(thisClass)
if let classIndex = thisClassIndex {
// Class label found, increment count
classificationData.classCount[classIndex] += 1
// Add offset of data point
classificationData.classOffsets[classIndex].append(index)
}
else {
// Class label not found, add it
classificationData.foundLabels.append(thisClass)
classificationData.classCount.append(1) // Start count at 1 - this instance
classificationData.classOffsets.append([index]) // First offset is this point
}
}

// Set the classification data as the optional data for the data set
optionalData = classificationData
}


// Leave here in case it is used by other methods
public static func gaussianRandom(mean : Double, standardDeviation : Double) -> Double
{
Expand Down
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