Comments (1)
Yea sure you may try for regression task as well, try with example below by changing target:
from tabgan.sampler import OriginalGenerator, GANGenerator
import pandas as pd
import numpy as np
# random input data
train = pd.DataFrame(np.random.randint(-10, 150, size=(150, 4)), columns=list("ABCD"))
target = pd.DataFrame(np.random.randint(0, 2, size=(150, 1)), columns=list("Y"))
test = pd.DataFrame(np.random.randint(0, 100, size=(100, 4)), columns=list("ABCD"))
# generate data
new_train1, new_target1 = OriginalGenerator().generate_data_pipe(train, target, test, )
new_train2, new_target2 = GANGenerator().generate_data_pipe(train, target, test, )
# example with all params defined
new_train3, new_target3 = GANGenerator(gen_x_times=1.1, cat_cols=None,
bot_filter_quantile=0.001, top_filter_quantile=0.999, is_post_process=True,
adversarial_model_params={
"metrics": "AUC", "max_depth": 2, "max_bin": 100,
"learning_rate": 0.02, "random_state": 42, "n_estimators": 500,
}, pregeneration_frac=2, only_generated_data=False,
gan_params = {"batch_size": 500, "patience": 25, "epochs" : 500,}).generate_data_pipe(train, target,
test, deep_copy=True, only_adversarial=False, use_adversarial=True)
Or may pass data without specific target just saying that target just another column, it should work
There 1 main difference between OriginalGenerator and GANGenerator - first generates data by sampling from original data, but GANGenerator uses GANs to generate data
from gan-for-tabular-data.
Related Issues (20)
- generated Cov is not that close HOT 2
- all sample codes not working till epoch end HOT 1
- second args in generate_data_pipe cannot be left None HOT 2
- TypeError: unsupported operand type(s) for +: 'NoneType' and 'NoneType' HOT 1
- training CTGAN stops in the middle (around 24%) HOT 2
- Difference between OriginalGenerator and GANGenerator HOT 1
- Getting this error when trying to install load HOT 2
- check HOT 1
- ContextualVersionConflict: (scikit-learn 1.0.2 (/usr/local/lib/python3.7/dist-packages), Requirement.parse('scikit-learn==0.23.2'), {'tabgan'}) HOT 3
- Dear Author, May I know the ctgan version for the installation? I am getting error. from ctgan import _CTGANSynthesizer ImportError: cannot import name '_CTGANSynthesizer' HOT 4
- pip install scikit-learn version issue HOT 3
- Mistake in Readme HOT 2
- Some issues araised when running Tab-GAN: 1) Manage Categorical Variables. 2) Batch size problem HOT 8
- Reproducibility issue HOT 1
- ValueError: Input X contains NaN although NaN filtered HOT 7
- IntCastingNaNError Despite No NaN values HOT 3
- LGBMClassifier.fit() got an unexpected keyword argument 'early_stopping_rounds' HOT 2
- Dependency issue with ForestDiffusion Generator HOT 3
- TypeError w/ Boolean Data HOT 1
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from gan-for-tabular-data.