CSCI-4830-002-2014 · indiesquidge · Nov 9, 2014 · Nov 10, 2014
diff --git a/.gitignore b/.gitignore
@@ -0,0 +1,4 @@
+yelp_dataset_challenge_academic_dataset
+tist
+ebird
+node_modules
diff --git a/README.md b/README.md
@@ -1,40 +1,40 @@
 # Name
 
-write-your-name
+Austin Wood
 
 # How many points have you earned?
 
-0/100
-
-(Make your own calculation and replace the number 0 with the points you think you've earned.)
+100/100
 
 # How many hours have you spent on this?
 
-fill-in-your-answer
+9 hours.
 
 # When did you first start working on this week's learning challenges?
 
-fill-in-your-answer
+Saturday November 8, 2014, 11:50pm
 
 # What is the most difficult part about this week's challenge?
 
-fill-in-your-answer
+The mongo files were huge, and some took forever to get into mongo. I don't really
+understand what we even learned in doing this mongo challenge; it just felt like 
+repetitive exercises...
 
 # Graph Database I
 
 ## Checkpoints (5 points x 3 = 15 points)
 
 ### 1. (5 point)
 
-![screenshot](screenshot.png)
+![checkpoint 1](img/neo4j_cp1.png?raw=true)
 
 ### 2. (5 point)
 
-![screenshot](screenshot.png)
+![chekcpoint 2](img/neo4j_cp2.png?raw=true)
 
 ### 3. (5 point)
 
-![screenshot](screenshot.png)
+![checkpoint 3](img/neo4j_cp3.png?raw=true)
 
 # MongoDB IV
 
@@ -44,66 +44,62 @@ fill-in-your-answer
 
 Count
 
-![screenshot](screenshot.png)
+![challenge 1a](img/mongo_ch1-count.png?raw=true)
 
 FindOne
 
-![screenshot](screenshot.png)
-
+![challenge 1b](img/mongo_ch1-findOne.png?raw=true)
 
 Query
 
-![screenshot](screenshot.png)
-
+![challenge 1c](img/mongo_ch1-query.png?raw=true)
 
 ### 2. (5 point)
 
 Count
 
-![screenshot](screenshot.png)
+![challenge 2a](img/mongo_ch2-count.png?raw=true)
 
 FindOne
 
-![screenshot](screenshot.png)
-
+![challenge 2b](img/mongo_ch2-findOne.png?raw=true)
 
 Query
 
-![screenshot](screenshot.png)
+![challenge 2c](img/mongo_ch2-query.png?raw=true)
 
 ### 3. (5 point)
 
 Count
 
-![screenshot](screenshot.png)
+![challenge 3a](img/mongo_ch3-count.png?raw=true)
 
 FindOne
 
-![screenshot](screenshot.png)
-
+![challenge 3b](img/mongo_ch3-findOne.png?raw=true)
 
 Query
 
-![screenshot](screenshot.png)
+![challenge 3c](img/mongo_ch3-query.png?raw=true)
 
 
 ### 4. (5 point)
 
 Count
 
-![screenshot](screenshot.png)
+![challenge 4a](img/mongo_ch4-count.png?raw=true)
 
 FindOne
 
-![screenshot](screenshot.png)
+![challenge 4b](img/mongo_ch4-findOne.png?raw=true)
 
 Query 1
 
-![screenshot](screenshot.png)
+![challenge 4c](img/mongo_ch4-query1.png?raw=true)
 
 Query 2
 
-![screenshot](screenshot.png)
+![challenge 4d](img/mongo_ch4-query2.png?raw=true)
 
 
 # Machine Learning III
@@ -112,141 +108,141 @@ Query 2
 
 ### 1. (5 point)
 
-![screenshot](screenshot.png)
+![checkpoint 1](img/machine_cp1.png?raw=true)
 
 ### 2. (5 point)
 
-![screenshot](screenshot.png)
+![screenshot](img/machine_cp2.png?raw=true)
 
 ## Challenges (5 points x 4 = 20 points)
 
 ### 1. (5 point)
 
-Accuracy = {fill-in-your-best-number}
+Accuracy = 75.0241
 
 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 = false; % Adds accelerometer features
+	add_gyroscope = true; % Adds gyroscope features
+	add_magneticField = true; % Adds magnetic field features
+	add_gravity = true; % Adds gravity features
+	add_linearAcceleration = false; % 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 = false; % 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 = 2; % Try different number of trees for the Random Forest classifier
+	sigma = 10; % 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 = 10; % Try different values of K for the K-nearest Neighbor classifier
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 ### 2. (5 point)
 
-Accuracy = {fill-in-your-best-number}
+Accuracy = 70.2025 
 
 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 = false; % Adds accelerometer features
+	add_gyroscope = true; % Adds gyroscope features
+	add_magneticField = true; % Adds magnetic field features
+	add_gravity = false; % Adds gravity features
+	add_linearAcceleration = false; % 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 = false; % 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 = 2; % 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 = 10; % Try different values of K for the K-nearest Neighbor classifier
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 ### 3. (5 point)
 
-Accuracy = {fill-in-your-best-number}
+Accuracy = 80.6172
 
 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 = false; % Adds accelerometer features
+	add_gyroscope = true; % Adds gyroscope features
+	add_magneticField = true; % Adds magnetic field features
+	add_gravity = true; % Adds gravity features
+	add_linearAcceleration = false; % 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 = false; % 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 = 2; % Try different number of trees for the Random Forest classifier
+	sigma = 10; % 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 = 10; % Try different values of K for the K-nearest Neighbor classifier
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 ### 4. (5 point)
 
-Accuracy = {fill-in-your-best-number}
+Accuracy = 76.5670
 
 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 = false; % Adds accelerometer features
+	add_gyroscope = true; % Adds gyroscope features
+	add_magneticField = true; % Adds magnetic field features
+	add_gravity = true; % Adds gravity features
+	add_linearAcceleration = false; % 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 = false; % 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 = 2; % Try different number of trees for the Random Forest classifier
+	sigma = 10; % 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 = 10; % 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)
+![challenge 1](img/d3_ch1.png?raw=true)
 
 ### 2. (5 point)
 
-![screenshot](screenshot.png)
+![challenge 2](img/d3_ch2.png?raw=true)
 
 ### 3. (5 point)
 
-![screenshot](screenshot.png)
+![challenge 2](img/d3_ch2.png?raw=true)
 
 ### 4. (5 point)
 
-![screenshot](screenshot.png)
+![challenge 2](img/d3_ch2.png?raw=true)
 
 ### 5. (5 point)
 
-![screenshot](screenshot.png)
+![challenge 2](img/d3_ch2.png?raw=true)
 
 ### 6. (5 point)
 
-![screenshot](screenshot.png)
+![challenge 2](img/d3_ch2.png?raw=true)
 
 ### 7. (5 point)
 
-![screenshot](screenshot.png)
+![challenge 2](img/d3_ch2.png?raw=true)
diff --git a/app.js b/app.js
@@ -3,21 +3,20 @@ 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://127.0.0.1:27017/yelp", {native_parser:true});
 
 app.engine('.html', require('ejs').__express);
 app.set('views', __dirname);
 app.set('view engine', 'html');
 
 app.get('/state/:state', function(req, res) {
-    var query = {"state" : req.params.state};
-    var projection = {};
-    db.collection('business')
-        .find(query,projection)
-        .limit(20)
-        .toArray(function (err, items) {        
-            res.render("business_map", {data: items});        
-    });
+  var query = {"state" : req.params.state};
+  var projection = {};
+  db.collection('businesses')
+  .find(query, projection)
+  .toArray(function (err, items) {
+    res.render("business_map", {data: items});
+  });
 });
 
 app.listen(3000);