Finished - Alexia Newgord

README.md

@@ -1,40 +1,42 @@
 # Name
 
-write-your-name
+Alexia Newgord
 
 # How many points have you earned?
 
-0/100
+100/100, but a day late
 
 (Make your own calculation and replace the number 0 with the points you think you've earned.)
 
 # How many hours have you spent on this?
 
-fill-in-your-answer
+8ish
 
 # When did you first start working on this week's learning challenges?
 
-fill-in-your-answer
+Wednesday
 
 # What is the most difficult part about this week's challenge?
 
-fill-in-your-answer
+I accidently imported the wrong dataset at one point, which took four hours.  Had problems converting csv into json and importing in one go due to mongo size restrictions, so instead I directly imported each row by converting it to json and passing it in one by one.
 
 # Graph Database I
 
 ## Checkpoints (5 points x 3 = 15 points)
 
 ### 1. (5 point)
 
-![screenshot](screenshot.png)
+to start: cd to the extracted folder, start with bin/neo4j start
+
+![screenshot](gcp1.png)
 
 ### 2. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](gcp2.png)
 
 ### 3. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](gcp3.png)
 
 # MongoDB IV
 
@@ -44,66 +46,66 @@ fill-in-your-answer
 
 Count
 
-![screenshot](screenshot.png)
+![screenshot](mc1a.png)
 
 FindOne
 
-![screenshot](screenshot.png)
+![screenshot](mc1b.png)
 
 
 Query
 
-![screenshot](screenshot.png)
+![screenshot](mc1c.png)
 
 
 ### 2. (5 point)
 
 Count
 
-![screenshot](screenshot.png)
+![screenshot](mc2a.png)
 
 FindOne
 
-![screenshot](screenshot.png)
+![screenshot](mc2b.png)
 
 
 Query
 
-![screenshot](screenshot.png)
+![screenshot](mc2c.png)
 
 ### 3. (5 point)
 
 Count
 
-![screenshot](screenshot.png)
+![screenshot](mc3a.png)
 
 FindOne
 
-![screenshot](screenshot.png)
+![screenshot](mc3b.png)
 
 
 Query
 
-![screenshot](screenshot.png)
+![screenshot](mc3c.png)
 
 
 ### 4. (5 point)
 
 Count
 
-![screenshot](screenshot.png)
+![screenshot](mc4a.png)
 
 FindOne
 
-![screenshot](screenshot.png)
+![screenshot](mc4b.png)
 
 Query 1
 
-![screenshot](screenshot.png)
+![screenshot](mc4c.png)
 
 Query 2
 
-![screenshot](screenshot.png)
+![screenshot](mc4d.png)
 
 
 # Machine Learning III
@@ -112,141 +114,141 @@ Query 2
 
 ### 1. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](mlcp1.png)
 
 ### 2. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](mlcp2.png)
 
 ## Challenges (5 points x 4 = 20 points)
 
 ### 1. (5 point)
 
-Accuracy = {fill-in-your-best-number}
+Accuracy = 82.7387
 
 Features/Parameters
 
 	%%%%%%%%% Choose feature source %%%%%%%%%%%
-	add_accelerometer = {TODO}; % Adds accelerometer features
-	add_gyroscope = {TODO}; % Adds gyroscope features
-	add_magneticField = {TODO}; % Adds magnetic field features
-	add_gravity = {TODO}; % Adds gravity features
-	add_linearAcceleration = {TODO}; % Adds linear acceleration features
-	add_orientation = {TODO}; % Adds azimuth, pich and roll features
-	add_light = {TODO}; % Adds light value
-	add_proximity = {TODO}; % Adds proximity value
-	add_studentID = {TODO}; % Adds student ID
+	add_accelerometer = true; % Adds accelerometer features
+	add_gyroscope = true; % Adds gyroscope features
+	add_magneticField = true; % Adds magnetic field features
+	add_gravity = true; % Adds gravity features
+	add_linearAcceleration = true; % Adds linear acceleration features
+	add_orientation = true; % Adds azimuth, pich and roll features
+	add_light = true; % Adds light value
+	add_proximity = true; % Adds proximity value
+	add_studentID = true; % Adds student ID
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-	 
+
 	%%%%%%%%% Choose machine learning classifier parameters %%%%%%%%%%%%%%%
-	numTrees = {TODO}; % Try different number of trees for the Random Forest classifier
-	sigma = {TODO}; % Try different values of sigma for the Support Vector Machine classifier
-	dist = {TODO}; % Try different distributions = {'normal', 'kernel', 'mvmn' , 'mn'} for Naive Bayes classifier
-	K = {TODO}; % Try different values of K for the K-nearest Neighbor classifier
+	numTrees = 1; % Try different number of trees for the Random Forest classifier
+	sigma = 1; % Try different values of sigma for the Support Vector Machine classifier
+	dist = 'normal'; % Try different distributions = {'normal', 'kernel', 'mvmn' , 'mn'} for Naive Bayes classifier
+	K = 1; % Try different values of K for the K-nearest Neighbor classifier
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 ### 2. (5 point)
 
-Accuracy = {fill-in-your-best-number}
+Accuracy = 71.5526
 
 Features/Parameters
 
 	%%%%%%%%% Choose feature source %%%%%%%%%%%
-	add_accelerometer = {TODO}; % Adds accelerometer features
-	add_gyroscope = {TODO}; % Adds gyroscope features
-	add_magneticField = {TODO}; % Adds magnetic field features
-	add_gravity = {TODO}; % Adds gravity features
-	add_linearAcceleration = {TODO}; % Adds linear acceleration features
-	add_orientation = {TODO}; % Adds azimuth, pich and roll features
-	add_light = {TODO}; % Adds light value
-	add_proximity = {TODO}; % Adds proximity value
-	add_studentID = {TODO}; % Adds student ID
+	add_accelerometer = true; % Adds accelerometer features
+	add_gyroscope = true; % Adds gyroscope features
+	add_magneticField = true; % Adds magnetic field features
+	add_gravity = true; % Adds gravity features
+	add_linearAcceleration = true; % Adds linear acceleration features
+	add_orientation = true; % Adds azimuth, pich and roll features
+	add_light = true; % Adds light value
+	add_proximity = true; % Adds proximity value
+	add_studentID = true; % Adds student ID
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-	 
+
 	%%%%%%%%% Choose machine learning classifier parameters %%%%%%%%%%%%%%%
-	numTrees = {TODO}; % Try different number of trees for the Random Forest classifier
-	sigma = {TODO}; % Try different values of sigma for the Support Vector Machine classifier
-	dist = {TODO}; % Try different distributions = {'normal', 'kernel', 'mvmn' , 'mn'} for Naive Bayes classifier
-	K = {TODO}; % Try different values of K for the K-nearest Neighbor classifier
+	numTrees = 1; % Try different number of trees for the Random Forest classifier
+	sigma = 1; % Try different values of sigma for the Support Vector Machine classifier
+	dist = 'kernel'; % Try different distributions = {'normal', 'kernel', 'mvmn' , 'mn'} for Naive Bayes classifier
+	K = 1; % Try different values of K for the K-nearest Neighbor classifier
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 ### 3. (5 point)
 
-Accuracy = {fill-in-your-best-number}
+Accuracy = 65.5738
 
 Features/Parameters
 
 	%%%%%%%%% Choose feature source %%%%%%%%%%%
-	add_accelerometer = {TODO}; % Adds accelerometer features
-	add_gyroscope = {TODO}; % Adds gyroscope features
-	add_magneticField = {TODO}; % Adds magnetic field features
-	add_gravity = {TODO}; % Adds gravity features
-	add_linearAcceleration = {TODO}; % Adds linear acceleration features
-	add_orientation = {TODO}; % Adds azimuth, pich and roll features
-	add_light = {TODO}; % Adds light value
-	add_proximity = {TODO}; % Adds proximity value
-	add_studentID = {TODO}; % Adds student ID
+	add_accelerometer = true; % Adds accelerometer features
+	add_gyroscope = false; % Adds gyroscope features
+	add_magneticField = true; % Adds magnetic field features
+	add_gravity = true; % Adds gravity features
+	add_linearAcceleration = true; % Adds linear acceleration features
+	add_orientation = true; % Adds azimuth, pich and roll features
+	add_light = false; % Adds light value
+	add_proximity = true; % Adds proximity value
+	add_studentID = true; % Adds student ID
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-	 
+
 	%%%%%%%%% Choose machine learning classifier parameters %%%%%%%%%%%%%%%
-	numTrees = {TODO}; % Try different number of trees for the Random Forest classifier
-	sigma = {TODO}; % Try different values of sigma for the Support Vector Machine classifier
-	dist = {TODO}; % Try different distributions = {'normal', 'kernel', 'mvmn' , 'mn'} for Naive Bayes classifier
-	K = {TODO}; % Try different values of K for the K-nearest Neighbor classifier
+	numTrees = 1; % Try different number of trees for the Random Forest classifier
+	sigma = 150; % Try different values of sigma for the Support Vector Machine classifier
+	dist = 'kernel'; % Try different distributions = {'normal', 'kernel', 'mvmn' , 'mn'} for Naive Bayes classifier
+	K = 1; % Try different values of K for the K-nearest Neighbor classifier
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 ### 4. (5 point)
 
-Accuracy = {fill-in-your-best-number}
+Accuracy = 87.1745
 
 Features/Parameters
 
 	%%%%%%%%% Choose feature source %%%%%%%%%%%
-	add_accelerometer = {TODO}; % Adds accelerometer features
-	add_gyroscope = {TODO}; % Adds gyroscope features
-	add_magneticField = {TODO}; % Adds magnetic field features
-	add_gravity = {TODO}; % Adds gravity features
-	add_linearAcceleration = {TODO}; % Adds linear acceleration features
-	add_orientation = {TODO}; % Adds azimuth, pich and roll features
-	add_light = {TODO}; % Adds light value
-	add_proximity = {TODO}; % Adds proximity value
-	add_studentID = {TODO}; % Adds student ID
+	add_accelerometer = true; % Adds accelerometer features
+	add_gyroscope = true; % Adds gyroscope features
+	add_magneticField = true; % Adds magnetic field features
+	add_gravity = true; % Adds gravity features
+	add_linearAcceleration = true; % Adds linear acceleration features
+	add_orientation = true; % Adds azimuth, pich and roll features
+	add_light = true; % Adds light value
+	add_proximity = true; % Adds proximity value
+	add_studentID = true; % Adds student ID
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-	 
+
 	%%%%%%%%% Choose machine learning classifier parameters %%%%%%%%%%%%%%%
-	numTrees = {TODO}; % Try different number of trees for the Random Forest classifier
-	sigma = {TODO}; % Try different values of sigma for the Support Vector Machine classifier
-	dist = {TODO}; % Try different distributions = {'normal', 'kernel', 'mvmn' , 'mn'} for Naive Bayes classifier
-	K = {TODO}; % Try different values of K for the K-nearest Neighbor classifier
+	numTrees = 50; % Try different number of trees for the Random Forest classifier
+	sigma = 150; % Try different values of sigma for the Support Vector Machine classifier
+	dist = 'kernel'; % Try different distributions = {'normal', 'kernel', 'mvmn' , 'mn'} for Naive Bayes classifier
+	K = 1; % Try different values of K for the K-nearest Neighbor classifier
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 
 # D3 (VI) (5 points x 7 = 35 points)
 
 ### 1. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](dcp1.png)
 
 ### 2. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](dcp2.png)
 
 ### 3. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](dcp3.png)
 
 ### 4. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](dcp4.png)
 
 ### 5. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](dcp5.png)
 
 ### 6. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](dcp6.png)
 
 ### 7. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](dcp7.png)

app.js

@@ -3,7 +3,7 @@ var express = require('express');
 var app = express();
 
 var mongo = require('mongoskin');
-var db = mongo.db("mongodb://{USERNAME}:{PASSWORD}@{SEVERURL}", {native_parser:true});
+var db = mongo.db("mongodb://localhost/yelp/:3000", {native_parser:true});
 
 app.engine('.html', require('ejs').__express);
 app.set('views', __dirname);
@@ -12,9 +12,10 @@ app.set('view engine', 'html');
 app.get('/state/:state', function(req, res) {
     var query = {"state" : req.params.state};
     var projection = {};
-    db.collection('business')
+    db.collection('businesses2')
         .find(query,projection)
-        .limit(20)
+        .limit(100)
+        .sort({"review_count" : -1 })
         .toArray(function (err, items) {        
             res.render("business_map", {data: items});        
     });