Commit 3380c8b5 authored by Chris's avatar Chris
Browse files

"confusion matrices"

parent 470af87d

server.py

+1 −1
Original line number Diff line number Diff line
@@ -82,7 +82,7 @@ def getTopFiveWords(): 


@app.route('/getConfusionMatrix', methods=["GET"])

def getConfusionMatrix():

    return ml.getConfusionMatrix();

    return ml.getConfusionMatrix()





# Run the app!

web/index.html

+3 −0
Original line number Diff line number Diff line
@@ -93,6 +93,9 @@ 
            </div>



            <br>

            <p>Confusion matrices: These values show what percent of the messages were designated as, respectively:<br>

                true negative, false positive, false positive, and true positive.

            </p>

            <div id="confusion_matrices">

                <p>Confusion matrices for each algorithm will go here</p>

            </div>

web/js/main.js

+30 −0
Original line number Diff line number Diff line
@@ -200,6 +200,7 @@ function getTopFiveWords() { 
function initializeIndex() {

    getTopAlgorithms();

    getTopFiveWords();

    getConfusionMatrices();

}



// when the Clear button is pressed, clear the message textarea
@@ -239,6 +240,35 @@ function loadAlgGraph(topAlgs){ 
    });

}



function getConfusionMatrices() {

    var url = "http://localhost:8080"

    var endpoint = "/getConfusionMatrix"



    var http = new XMLHttpRequest();



    http.open("GET", url + endpoint, true);

    http.setRequestHeader('Content-Type', 'application/json; charset=UTF-8');



    http.onreadystatechange = function () {

        var DONE = 4;       // 4 means that the request is done

        var OK = 200;       // 200 means a successful return



        if (http.readyState == DONE && http.status == OK && http.responseText) {

            // JSON string

            replyString = http.responseText;



            // JSON -> JS object

            replyObj = JSON.parse(replyString);



            document.getElementById("confusion_matrices").innerText = "Decision tree confusion matrix:\n" + replyObj["Decision Tree"] +

            "\nNeural Network confusion matrix:\n" + replyObj["Neural Network"] +

             "\nPerceptron confusion matrix:\n" + replyObj["Perceptron"] +

             "\nStochastic gradient descent confusion matrix:\n" + replyObj["Stochastic Gradient Descent"]

        }

    }

    http.send();

}



function loadWordGraph(topWords){



    Highcharts.chart('top_words', {