accord on f#?

accord.fs

open Accord.MachineLearning.FSharp
open Deedle

let data = [ ("D1",   "Sunny",      "Hot",       "High",   "Weak",    "No" )
             ("D2",   "Sunny",      "Hot",       "High",  "Strong",   "No" ) 
             ("D3",  "Overcast",    "Hot",       "High",   "Weak",    "Yes")
             ("D4",   "Rain",       "Mild",      "High",   "Weak",    "Yes") 
             ("D5",   "Rain",       "Cool",     "Normal",  "Weak",    "Yes") 
             ("D6",   "Rain",       "Cool",     "Normal", "Strong",   "No" ) 
             ("D7",  "Overcast",    "Cool",     "Normal", "Strong",   "Yes")
             ("D8",   "Sunny",      "Mild",      "High",   "Weak",    "No" )  
             ("D9",   "Sunny",      "Cool",     "Normal",  "Weak",    "Yes") 
             ("D10", "Rain",        "Mild",     "Normal",  "Weak",    "Yes") 
             ("D11",  "Sunny",      "Mild",     "Normal", "Strong",   "Yes")
             ("D12", "Overcast",    "Mild",      "High",  "Strong",   "Yes") 
             ("D13", "Overcast",    "Hot",      "Normal",  "Weak",    "Yes") 
             ("D14",  "Rain",       "Mild",      "High",  "Strong",   "No" ) ]

// build a data frame from the values above, then create a decision tree using the supplied list of inputs columns
// and an output column
let tree = data
           |> Frame.ofRecords
           |> Frame.indexColsWith [ "Day"; "Outlook"; "Temperature"; "Humidity"; "Wind"; "PlayTennis" ]
           |> buildDecisionTreeFromFrame [ "Outlook"; "Temperature"; "Humidity"; "Wind" ] "PlayTennis"

tree |> calculate [ "Rain"; "Hot"; "High"; "Strong" ] // "No"
tree |> calculate [ "Overcast"; "Hot"; "High"; "Strong" ] // "Yes"