import SVM

import ROC

import pandas as pd

# ------------------------------------- Data preparation -------------------------------------

data = pd.read_csv('iris.csv') # read data from file

# ------------------------------------- Setosa vs Versicolor ----------------------------------

dataTrain = data[10:50] # split data on train set and test set

dataTrain = dataTrain.append(data[50:90], ignore_index=True)

label = dataTrain.Species

label = label.replace(['setosa', 'versicolor'], ['1', '-1']) # replace setosa, versicolor with '-1', '1'

dataTrain.drop(['Species'], axis=1, inplace=True)

dataTest = data[0:10]

dataTest = dataTest.append(data[90:100], ignore_index=True)

target = dataTest.Species

target = target.replace(['setosa', 'versicolor'], ['1', '-1']) # replace setosa, versicolor with '-1', '1'

dataTest.drop(['Species'], axis=1, inplace=True)

model = SVM.SVM() # initialize model

model.train(dataTrain, label) # train model

predict = model.predict(dataTest) # get predict

ROC.ROC(predict, target, '-1') # plot ROC curve

# ----------------------------------- Versicolor vs Virginica -----------------------------------

import SVM

import ROC

import pandas as pd

# ------------------------------------- Data preparation -------------------------------------

data = pd.read_csv('iris.csv') # read data from file

# ------------------------------------- Setosa vs Versicolor ----------------------------------

dataTrain = data[10:50] # split data on train set and test set

dataTrain = dataTrain.append(data[50:90], ignore_index=True)

label = dataTrain.Species

label = label.replace(['setosa', 'versicolor'], ['1', '-1']) # replace setosa, versicolor with '1', '-1'

dataTrain.drop(['Species'], axis=1, inplace=True)

dataTest = data[0:10]

dataTest = dataTest.append(data[90:100], ignore_index=True)

target = dataTest.Species

target = target.replace(['setosa', 'versicolor'], ['1', '-1']) # replace setosa, versicolor with '1', '-1'

dataTest.drop(['Species'], axis=1, inplace=True)

model = SVM.SVM() # initialize model

model.train(dataTrain, label) # train model

predict = model.predict(dataTest) # get predict

ROC.ROC(predict, target, '1') # plot ROC curve

# ----------------------------------- Versicolor vs Virginica -----------------------------------

dataTrain = data[100:140]

dataTrain = dataTrain.append(data[50:90], ignore_index=True)

label = dataTrain.Species

label = label.replace(['versicolor', 'virginica'], ['1', '-1']) # replace versicolor, virginica with '1', '-1'

dataTrain.drop(['Species'], axis=1, inplace=True)

dataTest = data[90:100]

dataTest = dataTest.append(data[140:150], ignore_index=True)

target = dataTest.Species

target = target.replace(['versicolor', 'virginica'], ['1', '-1']) # replace versicolor, virginica with '1', '-1'

dataTest.drop(['Species'], axis=1, inplace=True)

model = SVM.SVM() # initialize model

model.train(dataTrain, label) # train model

predict = model.predict(dataTest) # get predict

ROC.ROC(predict, target, '1') # plot ROC curve

# ------------------------------------ Virginica vs Setosa -------------------------------------

dataTrain = data[100:140]

dataTrain = dataTrain.append(data[10:50], ignore_index=True)

label = dataTrain.Species

label = label.replace(['virginica', 'setosa'], ['1', '-1']) # replace virginica, setosa with '1', '-1'

dataTrain.drop(['Species'], axis=1, inplace=True)

dataTest = data[140:150]

dataTest = dataTest.append(data[0:10], ignore_index=True)

target = dataTest.Species

target = target.replace(['virginica', 'setosa'], ['1', '-1']) # replace virginica, setosa with '1', '-1'

dataTest.drop(['Species'], axis=1, inplace=True)

model = SVM.SVM() # initialize model

model.train(dataTrain, label) # train model

predict = model.predict(dataTest) # get predict

ROC.ROC(predict, target, '1') # plot ROC curve