sudipto80

//Calculates the standard deviation 
let stddev(list:float list)=
    sqrt (List.fold (fun acc elem -> acc + (float elem - List.average list) ** 2.0 ) 0.0
                     list / float list.Length)

let trueRanks = [1.;2.;3.;4.;5.;5.;7.;8.;9.;10.]
let predictedRanks = [1.;2.;3.;4.;6.;7.;5.;8.;10.;9.]
let uBar  =  trueRanks  |> List.average

let upBar = predictedRanks |> List.average

sudipto80

//Mean Absolute Error
let mae (ratings:float list)(predictions:float list) =
        (List.zip ratings predictions |> List.sumBy (fun t -> abs (fst t - snd t)))
                            /float ratings.Length

//Normalized Mean Absolute Error
let nmae (ratings:float list)(predictions:float list) =
   let rMax = ratings |> List.max
   let rMin = ratings |> List.min
   (mae ratings predictions )/(rMax - rMin)

sudipto80

let SimuDot (ratings :(float list)list) (a:int)(u:int)=
        let num =  List.zip ratings.[a] ratings.[u]
                       |> List.sumBy (fun item -> fst item * snd item)
        let d1 = ratings.[a] |> List.sumBy (fun item -> item  * item )
        let d2 = ratings.[u] |> List.sumBy (fun item -> item  * item )

        if d1 = 0.0 || d2 = 0.0 then 0.0 else num / (sqrt d1 * sqrt d2)

let ratings = [[4.;0.;5.;5.];[4.;2.;1.;0.];[3.;0.;2.;4.];[4.;4.;0.;0.];[2.;1.;3.;5.]]
SimuDot ratings 0 1

sudipto80

//Average rating for all other rated items by the user
//except the item "except"
let rBaru(u:float list)(except:int)=
    let filtered = u |> List.mapi(fun i j -> if i <> except then j else 0.0)
                     |> List.filter(fun t -> t <> 0.0)
    float ( List.sum filtered ) / float filtered.Length

//The following function finds the common item indices
let commonItemIndices (ratings:(float list)list)(a:int)(u:int)=

sudipto80

let x = [1.;2.;3.;4.;5.]
let y = [1.;2.;2.;3.;4.]
let z = [3;4]

let x_bar = List.average x
let y_bar = List.average y

let numerator = 
   List.zip x y
   |> List.sumBy (fun item -> (fst item - x_bar)*(snd item - y_bar))

sudipto80

//root mean squared error
let rmse(ratings:float list)(predictions:float list) =
      sqrt(( List.zip ratings predictions |> List.map (fun t -> fst t - snd t) |> List.sum )
          /(float predictions.Length ))

rmse [1.3;4.5] [4.1;0.41] |> Dump

sudipto80

Dictionary<string,List<string>> graph = 
       new Dictionary<string,List<string>>();

graph.Add("A",new List<string>(){"B","C","D"});
graph.Add("B",new List<string>(){"A","E","F"});
graph.Add("E",new List<string>(){"B","G"});

List<string> visited = new List<string>();
Queue<string> qu = new  Queue<string>();

sudipto80

void Main()
{
	BinarySearch(new int[]{1,3,4,5,9,10},1).Dump();
}

int BinarySearch(int[] array,int x)
{
	int low = 0;
	int high = array.Length - 1;
	

sudipto80

 #include <stdio.h>
 #include <string.h>
 #include <stdlib.h>
 #include <math.h>
 int jolly( int nums[], int length)
 {
             //Pre-conditions
             if(length <= 0 )
               return 0;
             int i;

sudipto80

string ops = "+-*/";
string vals = "1234567890";
Stack<char> opStack = new Stack<char>();
Stack<int> valStack = new Stack<int>();

void Main()
{

	string expr = "(1 + ((2+3)*(4*5)))";
	foreach (char c in expr)