Index

_

__init__() (pydis_nn.neuralnetwork.NeuralNetwork method)

C

calculate_dataset_statistics() (in module pydis_nn.data)

D

duplicate_rows (main.UploadResponse attribute)

E

epoch (main.LossHistoryItem attribute)

epochs_used (main.TrainResponse attribute) evaluate_all() (pydis_nn.neuralnetwork.NeuralNetwork method)

F

feature_ranges (main.UploadResponse attribute) feature_stats (main.UploadResponse attribute) FeatureRange (class in main)

features (main.PredictRequest attribute) FeatureStats (class in main) fit() (pydis_nn.neuralnetwork.NeuralNetwork method)

G

generate_sample_dataset() (in module pydis_nn.utils)

H

health_check() (in module main)

hidden_sizes (main.TrainRequest attribute) (pydis_nn.neuralnetwork.NeuralNetwork attribute)

L

learning_rate (main.TrainRequest attribute) (pydis_nn.neuralnetwork.NeuralNetwork attribute) load_and_preprocess() (in module pydis_nn.data) load_dataset() (in module pydis_nn.data)

load_raw_dataset() (in module pydis_nn.data) loss (main.LossHistoryItem attribute) loss_history (main.TrainResponse attribute) LossHistoryItem (class in main)

M

main module max (main.FeatureRange attribute) max_avg (main.FeatureStats attribute) max_iter (main.TrainRequest attribute) (pydis_nn.neuralnetwork.NeuralNetwork attribute) memory_usage_mb (main.UploadResponse attribute) message (main.TrainResponse attribute) (main.UploadResponse attribute) min (main.FeatureRange attribute) min_avg (main.FeatureStats attribute) missing_values (main.UploadResponse attribute) model (pydis_nn.neuralnetwork.NeuralNetwork attribute)

model_config (main.FeatureRange attribute) (main.FeatureStats attribute) (main.LossHistoryItem attribute) (main.PredictionSample attribute) (main.PredictRequest attribute) (main.PredictResponse attribute) (main.TrainRequest attribute) (main.TrainResponse attribute) (main.UploadResponse attribute) module main pydis_nn.data pydis_nn.neuralnetwork pydis_nn.utils

N

n_features (main.UploadResponse attribute)

n_samples (main.UploadResponse attribute) NeuralNetwork (class in pydis_nn.neuralnetwork)

P

pred (main.PredictionSample attribute) predict() (in module main) (pydis_nn.neuralnetwork.NeuralNetwork method) prediction (main.PredictResponse attribute) predictions_sample (main.TrainResponse attribute) PredictionSample (class in main) PredictRequest (class in main)

PredictResponse (class in main) pydis_nn.data module pydis_nn.neuralnetwork module pydis_nn.utils module

R

random_state (main.TrainRequest attribute) (pydis_nn.neuralnetwork.NeuralNetwork attribute)

root() (in module main)

S

score() (pydis_nn.neuralnetwork.NeuralNetwork method) split_data() (in module pydis_nn.data) standardize_features() (in module pydis_nn.data)

status (main.PredictResponse attribute) (main.TrainResponse attribute) (main.UploadResponse attribute)

T

target_max (main.FeatureStats attribute) target_mean (main.FeatureStats attribute) target_min (main.FeatureStats attribute) target_std (main.FeatureStats attribute) test_mse (main.TrainResponse attribute) test_r2 (main.TrainResponse attribute) test_size (main.TrainRequest attribute)

train_model() (in module main) train_mse (main.TrainResponse attribute) train_r2 (main.TrainResponse attribute) train_size (main.TrainRequest attribute) training_time_seconds (main.TrainResponse attribute) TrainRequest (class in main) TrainResponse (class in main) true (main.PredictionSample attribute)

U

upload_dataset() (in module main)

UploadResponse (class in main)

V

val_loss (main.LossHistoryItem attribute) val_mse (main.TrainResponse attribute)

val_r2 (main.TrainResponse attribute) val_size (main.TrainRequest attribute)