def fit(self,
fit_X,
fit_y,
batchsize=100,
n_epoch=200,
n_units1=512,
n_units2=128,
tv_ratio=0.95,
optimizerAlgorithm="Adam",
savefigName="result.pdf",
savemodelName="ListNet.model"):
train_X, train_y, validate_X, validate_y = self.splitData(
fit_X, fit_y, tv_ratio)
print("The number of data, train:", len(train_X), "validate:",
len(validate_X)) # 训练和测试数据集表示
if self.resumemodelName is None:
self.initializeModel(Model, train_X, n_units1, n_units2,
optimizerAlgorithm)
self.trainModel(train_X, train_y, validate_X, validate_y, n_epoch,
batchsize)
plot_result.acc(self.train_acc, self.test_acc)
plot_result.loss(self.train_loss, self.test_loss)
self.saveModels(savemodelName)
def fit(self, fit_X, fit_y, batchsize=100, n_iter=5000, n_units1=512, n_units2=128, tv_ratio=0.95, optimizerAlgorithm="Adam", savefigName="result1.pdf", savemodelName="RankNet.model"):
train_X, train_y, validate_X, validate_y = self.splitData(fit_X, fit_y, tv_ratio)
print("The number of data, train:", len(train_X), "validate:", len(validate_X))
if self.resumemodelName is None:
self.initializeModel(Model, train_X, n_units1, n_units2, optimizerAlgorithm)
self.trainModel(train_X, train_y, validate_X, validate_y, n_iter)
plot_result.acc(self.train_loss, self.test_loss, savename=savefigName)
self.saveModels(savemodelName)
def fit(self, fit_X, fit_y, batchsize=100, n_iter=5000, n_units1=512, n_units2=128, tv_ratio=0.95, optimizerAlgorithm="Adam", savefigName="result.pdf", savemodelName="RankNet.model"):
train_X, train_y, validate_X, validate_y = self.splitData(fit_X, fit_y, tv_ratio)
print("The number of data, train:", len(train_X), "validate:", len(validate_X))
if self.resumemodelName is None:
self.initializeModel(Model, train_X, n_units1, n_units2, optimizerAlgorithm)
self.trainModel(train_X, train_y, validate_X, validate_y, n_iter)
plot_result.acc(self.train_loss, self.test_loss, savename=savefigName)
self.saveModels(savemodelName)
def fit(self, fit_X, fit_y, batchsize=100, n_epoch=200, n_units1=512, n_units2=128, tv_ratio=0.95, optimizerAlgorithm="Adam", savefigName="result.pdf", savemodelName="ListNet.model"):
train_X, train_y, validate_X, validate_y = self.splitData(fit_X, fit_y, tv_ratio)
print("The number of data, train:", len(train_X), "validate:", len(validate_X)) # トレーニングとテストのデータ数を表示
if self.resumemodelName is None:
self.initializeModel(Model, train_X, n_units1, n_units2, optimizerAlgorithm)
self.trainModel(train_X, train_y, validate_X, validate_y, n_epoch, batchsize)
plot_result.acc(self.train_acc, self.test_acc)
plot_result.loss(self.train_loss, self.test_loss)
self.saveModels(savemodelName)
