Finished creating SimpleLinearRegression class (which allows the use …

…of 1 feature set and 1 set of output) and the PolynomialRegression class which allows for multiple features. The class have been tested on another example Xcode project, but unit tests will be coming soon

.gitmodules

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+[submodule "Carthage/Checkouts/Upsurge"]
+	path = Carthage/Checkouts/Upsurge
+	url = https://github.com/aleph7/Upsurge.git
+[submodule "Carthage/Checkouts/SwiftCSV"]
+	path = Carthage/Checkouts/SwiftCSV
+	url = https://github.com/naoty/SwiftCSV.git

Cartfile

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+github "aleph7/Upsurge"
+github "naoty/SwiftCSV"

Cartfile.resolved

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+github "naoty/SwiftCSV" "0.3.2"
+github "aleph7/Upsurge" "0.7.1"

DataManager.swift

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+//
+//  DataManager.swift
+//  MLKit
+//
+//  Created by Guled on 6/30/16.
+//  Copyright © 2016 Somnibyte. All rights reserved.
+//
+
+import Foundation
+import Upsurge
+
+/**
+ The Numeric Type Protocol allows for generic functions
+ to take in integers or doubles or floats.
+*/
+public protocol NumericType {
+    func +(lhs: Self, rhs: Self) -> Self
+    func -(lhs: Self, rhs: Self) -> Self
+    func *(lhs: Self, rhs: Self) -> Self
+    func /(lhs: Self, rhs: Self) -> Self
+    func %(lhs: Self, rhs: Self) -> Self
+    init(_ v: Int)
+}
+
+
+extension Double : NumericType { }
+extension Float  : NumericType { }
+extension Int    : NumericType { }
+extension Int8   : NumericType { }
+extension Int16  : NumericType { }
+extension Int32  : NumericType { }
+extension Int64  : NumericType { }
+extension UInt   : NumericType { }
+extension UInt8  : NumericType { }
+extension UInt16 : NumericType { }
+extension UInt32 : NumericType { }
+extension UInt64 : NumericType { }
+
+
+public class MLDataManager{
+
+
+    enum MLDataHandelingError: ErrorType {
+
+    }
+
+
+    /**
+     Description Goes Here
+     
+     @param
+     
+     @return 
+     
+     */
+    public static func sumUpData<T: NumericType> (data: Array<T>) -> T {
+        var sum = T(0)
+        for val  in data{
+            sum = sum + val
+        }
+        return sum
+    }
+
+    /**
+     Description Goes Here
+     
+     @param
+     
+     @return
+     
+     */
+    public static func mean<T: NumericType> (data: Array<T>) -> T {
+        let totalSum = sumUpData(data)
+        let totalAmountOfData = T(data.count)
+        return totalSum/totalAmountOfData
+    }
+
+    public static func dataToMatrix (features:[Array<Float>], output: Array<Float>) -> (Matrix<Float>,ValueArray<Float>) {
+
+
+        // Create Output Matrix 
+        let output_matrix = Matrix<Float>(rows:output.count, columns: 1, elements:output)
+
+        // Create "contant/intercept" list 
+        let contant_array = [Float](count: features[0].count, repeatedValue: 1.0)
+        var matrix_as_array:[[Float]] = []
+
+        for (i, _) in contant_array.enumerate() {
+            var new_row:[Float] = []
+            new_row.append(contant_array[i])
+
+            for feature_array in features {
+                new_row.append(feature_array[i])
+            }
+
+            matrix_as_array.append(new_row)
+        }
+
+        let feature_matrix = Matrix<Float>(matrix_as_array)
+
+        return (feature_matrix, output_matrix.elements)
+    }
+
+
+
+}
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+

LICENSE

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+The license can be found here: https://creativecommons.org/licenses/by/4.0/