From 79c49f0b1dda130fb98e67473beb2646205caec4 Mon Sep 17 00:00:00 2001 From: DidierRLopes Date: Mon, 22 Mar 2021 02:22:43 +0000 Subject: [PATCH] Update prediction readme --- gamestonk_terminal/prediction_techniques/README.md | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/gamestonk_terminal/prediction_techniques/README.md b/gamestonk_terminal/prediction_techniques/README.md index bb0a829d05e..0b9b74b17e9 100644 --- a/gamestonk_terminal/prediction_techniques/README.md +++ b/gamestonk_terminal/prediction_techniques/README.md @@ -24,6 +24,7 @@ This menu aims to predict the share price of a pre-loaded stock, and the usage o - MultiLayer Perceptron * [rnn](#rnn) - Recurrent Neural Network + - Contains a [looping example](#looping) * [lstm](#lstm) - Long-Short Term Memory - Contains a [backtesting example](#backtesting) @@ -168,6 +169,7 @@ MulitLayer Perceptron: * --xla_gpu: if present, will enable XLA for GPU (overrides environment variables during run). * --force_allow_gpu_growth: if true, will force TensorFlow to allow GPU memory usage to grow as needed. Otherwise will allocate 100% of available GPU memory when CUDA is set up. Default true. * --batch_size: batch size for model training, should not be used unless advanced user. Default None. + * --loops: number of loops to iterate and train models. Default 1. Due to the complexity of defining a model through command line, one can define it in: [config_neural_network_models.txt](/config_neural_network_models.py) ``` @@ -204,6 +206,7 @@ Recurrent Neural Network: * --xla_gpu: if present, will enable XLA for GPU (overrides environment variables during run). * --force_allow_gpu_growth: if true, will force TensorFlow to allow GPU memory usage to grow as needed. Otherwise will allocate 100% of available GPU memory when CUDA is set up. Default true. * --batch_size: batch size for model training, should not be used unless advanced user. Default None. + * --loops: number of loops to iterate and train models. Default 1. Due to the complexity of defining a model through command line, one can define it in: [config_neural_network_models.txt](/config_neural_network_models.py) ``` @@ -222,6 +225,13 @@ Recurrent_Neural_Network \ ![rnn](https://user-images.githubusercontent.com/25267873/108604940-d0d12700-73a8-11eb-837e-a5aa128942d9.png) +### Looping Example + +![loops](https://user-images.githubusercontent.com/25267873/111932423-479b3600-8ab5-11eb-9d0b-7210d5f02e83.png) + +Captura de ecrã 2021-03-22, às 02 14 38 + + ## lstm ``` usage: lstm [-d N_DAYS] [-i N_INPUTS] [-j N_JUMPS] [-e N_EPOCHS] [-p {normalization,standardization,none}] @@ -240,6 +250,7 @@ Long-Short Term Memory: * --xla_gpu: if present, will enable XLA for GPU (overrides environment variables during run). * --force_allow_gpu_growth: if true, will force TensorFlow to allow GPU memory usage to grow as needed. Otherwise will allocate 100% of available GPU memory when CUDA is set up. Default true. * --batch_size: batch size for model training, should not be used unless advanced user. Default None. + * --loops: number of loops to iterate and train models. Default 1. Due to the complexity of defining a model through command line, one can define it in: [config_neural_network_models.py](/config_neural_network_models.py) ```