{"cells":[{"metadata":{"_uuid":"b0e63a134f9441ab16f619bdf1b179453d96d01e","_execution_state":"idle","trusted":true},"cell_type":"code","source":"## Importing packages\n\nlibrary(tidyverse) # metapackage with lots of helpful functions\nlibrary(rpart) #Decision tree\ntrain <- read_csv(\"../input/train.csv\")\ntest <- read_csv(\"../input/test.csv\")\n\n#Decision Tree model\ntraining.model <- rpart(label~.,data = train, method = \"class\")\n\n#Predicting Test \ntest_predict <- predict(training.model, test, type=\"class\")\n\n#Solution\nsubmission <- data.frame(ImageID=1:28000,Label=test_predict)\nwrite.csv(submission, file= \"mnist_dtree.csv\", row.names = F)\n\n#Applying random forest model\nlibrary(randomForest)\nset.seed(404)\nmodel_rf <- randomForest(as.factor(label)~.,data = train,method = \"rf\", ntree=25)\n\n#Predicting Test \ntest_predict_rf <- predict(model_rf, test)\n\n#Solution\nsubmission_rf <- data.frame(ImageID=1:28000,Label=test_predict_rf)\nwrite.csv(submission_rf, file= \"mnist_rf.csv\", row.names = F)\n\n#Running SVM\nlibrary(e1071)\nsvm_model <- svm(label~., data = train,type=\"C-classification\", kernel=\"polynomial\")\n\n#Predicting Test\ntest_predict_svm <- predict(svm_model, test)\n\n#Solution\nsubmission_svm <- data.frame(ImageID=1:28000,Label=test_predict_svm)\nwrite.csv(submission_svm, file=\"mnist_svm.csv\",row.names=F)","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"R","language":"R","name":"ir"},"language_info":{"mimetype":"text/x-r-source","name":"R","pygments_lexer":"r","version":"3.4.2","file_extension":".r","codemirror_mode":"r"}},"nbformat":4,"nbformat_minor":1}