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Text Classification

Text Classification

clear 
clc
emb = fastTextWordEmbedding;
                    

filenameTrain = "weatherReportsTrain.csv";
                    
textName = "event_narrative";
labelName = "event_type";
ttdsTrain = tabularTextDatastore(filenameTrain,'SelectedVariableNames',[textName labelName]);
                    

ttdsTrain.ReadSize = 8;
preview(ttdsTrain)

                            ans = 8×2 table 
                        
                                        event_narrative
                                    
                                        event_type
                                
                                        1
                                    
                                        'Large tree down between Plantersville and Nettleton.'
                                    
                                        'Thunderstorm Wind'
                                
                                        2
                                    
                                        'One to two feet of deep standing water developed on a street on the Winthrop University campus after more than an inch of rain fell in less than an hour. One vehicle was stalled in the water.'
                                    
                                        'Heavy Rain'
                                
                                        3
                                    
                                        'NWS Columbia relayed a report of trees blown down along Tom Hall St.'
                                    
                                        'Thunderstorm Wind'
                                
                                        4
                                    
                                        'Media reported two trees blown down along I-40 in the Old Fort area.'
                                    
                                        'Thunderstorm Wind'
                                
                                        5
                                    
                                        'A few tree limbs greater than 6 inches down on HWY 18 in Roseland.'
                                    
                                        'Thunderstorm Wind'
                                
                                        6
                                    
                                        'Awning blown off a building on Lamar Avenue. Multiple trees down near the intersection of Winchester and Perkins.'
                                    
                                        'Thunderstorm Wind'
                                
                                        7
                                    
                                        'Tin roof ripped off house on Old Memphis Road near Billings Drive. Several large trees down in the area.'
                                    
                                        'Thunderstorm Wind'
                                
                                        8
                                    
                                        'Powerlines down at Walnut Grove and Cherry Lane roads.'
                                    
                                        'Thunderstorm Wind'

	event_narrative	event_type
1	'Large tree down between Plantersville and Nettleton.'	'Thunderstorm Wind'
2	'One to two feet of deep standing water developed on a street on the Winthrop University campus after more than an inch of rain fell in less than an hour. One vehicle was stalled in the water.'	'Heavy Rain'
3	'NWS Columbia relayed a report of trees blown down along Tom Hall St.'	'Thunderstorm Wind'
4	'Media reported two trees blown down along I-40 in the Old Fort area.'	'Thunderstorm Wind'
5	'A few tree limbs greater than 6 inches down on HWY 18 in Roseland.'	'Thunderstorm Wind'
6	'Awning blown off a building on Lamar Avenue. Multiple trees down near the intersection of Winchester and Perkins.'	'Thunderstorm Wind'
7	'Tin roof ripped off house on Old Memphis Road near Billings Drive. Several large trees down in the area.'	'Thunderstorm Wind'
8	'Powerlines down at Walnut Grove and Cherry Lane roads.'	'Thunderstorm Wind'

labels = readLabels(ttdsTrain,labelName);
                    
classNames = unique(labels);
                    
numObservations = numel(labels);

                            sequenceLength = 100;
                            tdsTrain = transform(ttdsTrain, @(data) transformTextData(data,sequenceLength,emb,classNames))
                        
tdsTrain = 
 TransformedDatastore with properties:
                                UnderlyingDatastore: [1×1 matlab.io.datastore.TabularTextDatastore]
                                Transforms: {@(data)transformTextData(data,sequenceLength,emb,classNames)}
                                IncludeInfo: 0
                            

preview(tdsTrain)

                                ans = 8×2 table 
                            
                                            s.no
                                        
                                            predictors
                                        
                                            responses
                                    
                                            1
                                        
                                            1×100×300 single
                                        
                                            Thunderstorm Wind
                                    
                                            2
                                        
                                            1×100×300 single
                                        
                                            Heavy Rain
                                    
                                            3
                                        
                                            1×100×300 single
                                        
                                            Thunderstorm Wind
                                    
                                            4
                                        
                                            1×100×300 single
                                        
                                            Thunderstorm Wind
                                    
                                            5
                                        
                                            1×100×300 single
                                        
                                            Thunderstorm Wind
                                    
                                            6
                                        
                                            1×100×300 single
                                        
                                            Thunderstorm Wind
                                    
                                            7
                                        
                                            1×100×300 single
                                        
                                            Thunderstorm Wind
                                    
                                            8
                                        
                                            1×100×300 single
                                        
                                            Thunderstorm Wind

s.no	predictors	responses
1	1×100×300 single	Thunderstorm Wind
2	1×100×300 single	Heavy Rain
3	1×100×300 single	Thunderstorm Wind
4	1×100×300 single	Thunderstorm Wind
5	1×100×300 single	Thunderstorm Wind
6	1×100×300 single	Thunderstorm Wind
7	1×100×300 single	Thunderstorm Wind
8	1×100×300 single	Thunderstorm Wind

filenameValidation = "weatherReportsValidation.csv";
                    
                            ttdsValidation = tabularTextDatastore(filenameValidation,'SelectedVariableNames',[textName labelName]);
                    
tdsValidation = transform(ttdsValidation, @(data) transformTextData(data,sequenceLength,emb,classNames));

                        numFeatures = emb.Dimension;
                        inputSize = [1 sequenceLength numFeatures];
                        numFilters = 200;
                    
ngramLengths = [2 3 4 5 6];
                        
numBlocks = numel(ngramLengths);
                    
numClasses = numel(classNames);
                    

layer = imageInputLayer(inputSize,'Normalization','none','Name','input');
lgraph = layerGraph(layer);
                    

%create a block of convolution
                        
% a block 

                        % block of 
                    

                        % of convolution
% For each of the n-gram lengths, create a block of convolution, batch normalization, 
                    
% ReLU, dropout, and max pooling layers. Connect each block to the input layer.
                    
for j = 1:numBlocks
                    
    N = ngramLengths(j);
    block = [
        convolution2dLayer([1 N],numFilters,'Name',"conv"+N,'Padding','same')
        batchNormalizationLayer('Name',"bn"+N)
        reluLayer('Name',"relu"+N)
        dropoutLayer(0.2,'Name',"drop"+N)
        maxPooling2dLayer([1 sequenceLength],'Name',"max"+N)];
    lgraph = addLayers(lgraph,block);
                    
    lgraph = connectLayers(lgraph,'input',"conv"+N);
end

View the network architecture in a plot.

figure

plot(lgraph)

title("Network Architecture")

layers = [

depthConcatenationLayer(numBlocks,'Name','depth')

fullyConnectedLayer(numClasses,'Name','fc')

softmaxLayer('Name','soft')

classificationLayer('Name','classification')];

lgraph = addLayers(lgraph,layers);

figure

plot(lgraph)

title("Network Architecture")

for j = 1:numBlocks

N = ngramLengths(j);

lgraph = connectLayers(lgraph,"max"+N,"depth/in"+j);

end

figure

plot(lgraph)

title("Network Architecture")

Training Network

miniBatchSize = 128;
numIterationsPerEpoch = floor(numObservations/miniBatchSize);
                    
options = trainingOptions('adam', ...
                    
    'MaxEpochs',10, ...
    'MiniBatchSize',miniBatchSize, ...
    'ValidationData',tdsValidation, ...
'ValidationFrequency',numIterationsPerEpoch, ...
'Plots','training-progress', ...
'Verbose',false);
                    

net = trainNetwork(tdsTrain,lgraph,options);

Warning: Input datastore is not Shuffleable but trainingOptions specified shuffling. Training will proceed without shuffling.

Testing Network

filenameTest = "weatherReportsTest.csv";
ttdsTest = tabularTextDatastore(filenameTest,'SelectedVariableNames',[textName labelName]);
                        

                            tdsTest = transform(ttdsTest, @(data) transformTextData(data,sequenceLength,emb,classNames))
                        
tdsTest = 
 TransformedDatastore with properties:

                                UnderlyingDatastore: [1×1 matlab.io.datastore.TabularTextDatastore]
                                Transforms: {@(data)transformTextData(data,sequenceLength,emb,classNames)}
                                IncludeInfo: 0
                            

labelsTest = readLabels(ttdsTest,labelName);
YTest = categorical(labelsTest,classNames);
YPred = classify(net,tdsTest);
                    
accuracy = mean(YPred == YTest)
accuracy =  0.885463599715438