Feat/hyperparameter opt guide

[hrzn]

• New notebook showcasing an example of hyperparameter search with Optuna
• New section in user guide on hyperparameter search

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Codecov Report

Base: 93.88% // Head: 93.87% // Decreases project coverage by -0.00% ⚠️

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Additional details and impacted files

@@            Coverage Diff             @@
##           master    #1242      +/-   ##
==========================================
- Coverage   93.88%   93.87%   -0.01%     
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  Files          73       73              
  Lines        8097     8085      -12     
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- Hits         7602     7590      -12     
  Misses        495      495              

Impacted Files	Coverage Δ
darts/timeseries.py	92.34% <0.00%> (-0.06%)	⬇️
...arts/models/forecasting/torch_forecasting_model.py	87.45% <0.00%> (-0.05%)	⬇️
darts/models/forecasting/block_rnn_model.py	98.24% <0.00%> (-0.04%)	⬇️
darts/models/forecasting/nhits.py	99.27% <0.00%> (-0.01%)	⬇️

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[dennisbader]

Really cool stuff, thanks @hrzn !
Just added a few minor suggestions.
P.s. I wonder why TCNModel performs worse with the dayofweek cyclic encoder :D
Did you by any chance check if it performs similarly with the datetime attribute encoder?

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dennisbader commented on 2022-09-25T13:50:21Z
----------------------------------------------------------------

This is a quite demanding requirements,

-> This is a quite demanding task,

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dennisbader commented on 2022-09-25T13:50:22Z
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isort:

%matplotlib inline
import numpy as np

import matplotlib.pyplot as plt

import optuna

import random

import torch

from optuna.integration import PyTorchLightningPruningCallback

from optuna.visualization import (

plot_contour,

plot_optimization_history,

plot_param_importances,

)

from pytorch_lightning.callbacks import Callback, EarlyStopping

from sklearn.preprocessing import MaxAbsScaler

from tqdm.notebook import tqdm
from darts.dataprocessing.transformers import Scaler

from darts.datasets import ElectricityDataset

from darts.metrics import smape

from darts.models import TCNModel, LinearRegressionModel

from darts.utils.likelihood_models import GaussianLikelihood

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dennisbader commented on 2022-09-25T13:50:22Z
----------------------------------------------------------------

it consists in using these hyperparameters to build a model

-> it consists of using these hyperparameters to build a model

[hrzn]

Really cool stuff, thanks @hrzn ! Just added a few minor suggestions. P.s. I wonder why TCNModel performs worse with the dayofweek cyclic encoder :D Did you by any chance check if it performs similarly with the datetime attribute encoder?

Unfortunately I didn't experiment much with it. It's possible that this final config is still somewhat unlucky and using the dayofweek could still help a bit... Would be nice to try it out :)