ilovejs

Movie Recommendations with k-Nearest Neighbors and Cosine Similarity

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Introduction

The k-nearest neighbors (k-NN) algorithm is among the simplest algorithms in the data mining field. Distances / similarities are calculated between each element in the data set using some distance / similarity metric ^^[1]^ that the researcher chooses (there are many distance / similarity metrics), where the distance / similarity between any two elements is calculated based on the two elements' attributes. A data element’s k-NN are the k closest data elements according to this distance / similarity.

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1. A distance metric measures distance; the higher the distance the further apart the neighbors. A similarity metric measures similarity; the higher the similarity the closer the neighbors.

mythz

using System;
using ServiceStack.OrmLite;
using ServiceStack.Text;

namespace ConsoleApplication2
{
    public class TableA
    {
        public int Id { get; set; }
        public string Name { get; set; }

mikebluestein

namespace FSHelloSceneKit
    
open System
open MonoTouch.UIKit
open MonoTouch.Foundation
open MonoTouch.SceneKit
 
type FSHelloSceneKitViewController () =
    inherit UIViewController()
   

gallais

Require Import NArith.

Fixpoint sum_of (f : nat -> nat) (n : nat) : nat :=
match n with
  | O   => f O
  | S m => f (S m) + sum_of f m
end.

Lemma sum_of_pow : forall n,
 S (sum_of (NPeano.pow 2) n) = NPeano.pow 2 (S n).

gmorpheme

(ns ^{:doc "Loose translation of evaluator from chapter three
            of Lisp in Small Pieces into Clojure."}
  lispic.chapter3.cont
  (:refer-clojure :exclude [invoke])
  (:require [clojure.test :refer [deftest is]]))

(declare evaluate wrong)

(defn wrong [& args]
  (println args)

WillSewell

AsyncTest.define("webhook-channel-vacated #{params[:cluster_name]}", checks: 4, timeout: params[:timeout] ) { |t|
  channel_name = "channel-existence-#{rand(1000000)}"
  
  params[:webhooks]["/#{params[:cluster_name]}/webhook-channel-vacated"]=Proc.new do |post|
    next unless channel_name == (post["events"][0]["channel"] rescue nil)
    begin
      event_name = post["events"][0]["name"]
      pattern = {
        "time_ms" => matches{|x| x.kind_of?(Integer)},
        "events" => [{ "channel" => channel_name, "name" => event_name }]

mrluanma

import os
import errno
import urllib
import re
from urlparse import urlparse
from hashlib import md5
import httplib2
from lxml import html

hyone

;; hyone's solution to Merge with a Function
;; https://4clojure.com/problem/69

(fn my-merge-with [f & maps]
  (reduce
    (fn [a b]
      (reduce
        (fn [x [k v]]
          (assoc x k (if (b k) (f v (b k)) v)))
        b a))

mrluanma

# -*- encoding: utf-8 -*-
import os
import urlparse
import requests
from oauth_hook import OAuthHook


REQUEST_TOKEN_URL = 'http://api.t.sina.com.cn/oauth/request_token'
ACCESS_TOKEN_URL = 'http://api.t.sina.com.cn/oauth/access_token'
AUTHORIZE_URL = 'http://api.t.sina.com.cn/oauth/authorize'

skeptomai

196200_A Programming Language.pdf
1996-The Log-Structured Merge-Tree (LSM-Tree).pdf
6.05.HowToBeCreative.pdf
A tour of Scheme in Gambit.pdf
ABCDs of Paxos.pdf
AMQP Spec 0.8.pdf
Abstract Computing Machines.pdf
Adam's Advice and Reading List for High Tech Startup Entrepeneurs.pdf
Advanced Programming in the Unix Environment.pdf
Advanced encryption standard.PDF