コード例 #1
0
ファイル: combination.py プロジェクト: foolchi/Recommendation
    def calculate(self):
        self.allPredicts = np.zeros((4, self.testSize))

        bias = Bias(self.trainData, self.testData)
        bias.calculateBias()
        answers, predicts = bias.predict()
        self.biasClass = bias
        self.allPredicts[0, :] = predicts
        #print("Bias: %f" % evaluationRMSE(answers, predicts))

        similarity = Similarity(self.trainData, self.testData)
        similarity.calculateBias()
        similarity.calcSimiMatrix()
        answers, predicts = similarity.predict()
        self.similarityClass = similarity
        self.allPredicts[1, :] = predicts
        #print("Similarity: %f" % evaluationRMSE(answers, predicts))

        svd = SVD(self.trainData, self.testData)
        svd.generaterMat()
        svd.calcSVD()
        answers, predicts = svd.predict()
        self.svdClass = svd
        self.allPredicts[2, :] = predicts
        #print("SVD: %f" % evaluationRMSE(answers, predicts))

        matFactory = MatFactory(self.trainData, self.testData)
        matFactory.train(10, 11)
        answers, predicts = matFactory.predict()
        self.matFactoryClass = matFactory
        self.allPredicts[3, :] = predicts
        #print("MatFactory: %f" % evaluationRMSE(answers, predicts))

        pickleFile = open(predictsFile, 'wb')
        pickle.dump(self.allPredicts, pickleFile)
    def calculate(self):
        self.allPredicts = np.zeros((4, self.testSize))

        bias = Bias(self.trainData, self.testData)
        bias.calculateBias()
        answers, predicts = bias.predict()
        self.biasClass = bias
        self.allPredicts[0, :] = predicts
        #print("Bias: %f" % evaluationRMSE(answers, predicts))

        similarity = Similarity(self.trainData, self.testData)
        similarity.calculateBias()
        similarity.calcSimiMatrix()
        answers, predicts = similarity.predict()
        self.similarityClass = similarity
        self.allPredicts[1, :] = predicts
        #print("Similarity: %f" % evaluationRMSE(answers, predicts))

        svd = SVD(self.trainData, self.testData)
        svd.generaterMat()
        svd.calcSVD()
        answers, predicts = svd.predict()
        self.svdClass = svd
        self.allPredicts[2, :] = predicts
        #print("SVD: %f" % evaluationRMSE(answers, predicts))

        matFactory = MatFactory(self.trainData, self.testData)
        matFactory.train(10, 11)
        answers, predicts = matFactory.predict()
        self.matFactoryClass = matFactory
        self.allPredicts[3, :] = predicts
        #print("MatFactory: %f" % evaluationRMSE(answers, predicts))

        pickleFile = open(predictsFile, 'wb')
        pickle.dump(self.allPredicts, pickleFile)
コード例 #3
0
    def calAll(self):
        self.errs = [0] * 5
        bias = Bias(self.data, self.test)
        bias.calculateBias()
        answers, predicts = bias.predict()
        err = evaluationRMSE(answers, predicts)
        self.errs[0] = err
        print("Bias: %f" % err)

        similarity = Similarity(self.data, self.test)
        similarity.calculateBias()
        similarity.calcSimiMatrix()
        answers, predicts = similarity.predict()
        err = evaluationRMSE(answers, predicts)
        self.errs[1] = err
        print("Similarity: %f" % err)

        svd = SVD(self.data, self.test)
        svd.generaterMat()
        svd.calcSVD()
        answers, predicts = svd.predict()
        err = evaluationRMSE(answers, predicts)
        self.errs[2] = err
        print("SVD: %f" % err)

        matFactory = MatFactory(self.data, self.test)
        matFactory.train(20, 35)
        answers, predicts = matFactory.predict()
        err = evaluationRMSE(answers, predicts)
        self.errs[3] = err
        print("MatFactory: %f" % evaluationRMSE(answers, predicts))

        combination = Combination(self.data)
        combination.separateData()
        combination.calculate()
        combination.train(alpha=0.01, iter=10000)
        answers, predicts = combination.predict(self.test)
        err = evaluationRMSE(answers, predicts)
        self.errs[4] = err
        print("Combination: %f" % err)
        return self.errs
コード例 #4
0
ファイル: CalAll.py プロジェクト: foolchi/Recommendation
    def calAll(self):
        self.errs = [0] * 5
        bias = Bias(self.data, self.test)
        bias.calculateBias()
        answers, predicts = bias.predict()
        err = evaluationRMSE(answers, predicts)
        self.errs[0] = err
        print("Bias: %f" % err)

        similarity = Similarity(self.data, self.test)
        similarity.calculateBias()
        similarity.calcSimiMatrix()
        answers, predicts = similarity.predict()
        err = evaluationRMSE(answers, predicts)
        self.errs[1] = err
        print("Similarity: %f" % err)

        svd = SVD(self.data, self.test)
        svd.generaterMat()
        svd.calcSVD()
        answers, predicts = svd.predict()
        err = evaluationRMSE(answers, predicts)
        self.errs[2] = err
        print("SVD: %f" % err)

        matFactory = MatFactory(self.data, self.test)
        matFactory.train(20, 35)
        answers, predicts = matFactory.predict()
        err = evaluationRMSE(answers, predicts)
        self.errs[3] = err
        print("MatFactory: %f" % evaluationRMSE(answers, predicts))

        combination = Combination(self.data)
        combination.separateData()
        combination.calculate()
        combination.train(alpha = 0.01, iter = 10000)
        answers, predicts = combination.predict(self.test)
        err = evaluationRMSE(answers, predicts)
        self.errs[4] = err
        print("Combination: %f" % err)
        return self.errs