144 lines
2.9 KiB
YAML
144 lines
2.9 KiB
YAML
# Model Configuration
|
|
|
|
# XGBoost Settings
|
|
xgboost:
|
|
base:
|
|
n_estimators: 200
|
|
max_depth: 5
|
|
learning_rate: 0.05
|
|
subsample: 0.8
|
|
colsample_bytree: 0.8
|
|
gamma: 0.1
|
|
reg_alpha: 0.1
|
|
reg_lambda: 1.0
|
|
min_child_weight: 3
|
|
tree_method: "hist"
|
|
device: "cuda"
|
|
random_state: 42
|
|
|
|
hyperparameter_search:
|
|
n_estimators: [100, 200, 300, 500]
|
|
max_depth: [3, 5, 7]
|
|
learning_rate: [0.01, 0.05, 0.1]
|
|
subsample: [0.7, 0.8, 0.9]
|
|
colsample_bytree: [0.7, 0.8, 0.9]
|
|
|
|
gpu:
|
|
max_bin: 512
|
|
predictor: "gpu_predictor"
|
|
|
|
# GRU Settings
|
|
gru:
|
|
architecture:
|
|
hidden_size: 128
|
|
num_layers: 2
|
|
dropout: 0.2
|
|
recurrent_dropout: 0.1
|
|
use_attention: true
|
|
attention_heads: 8
|
|
attention_units: 128
|
|
|
|
training:
|
|
epochs: 100
|
|
batch_size: 256
|
|
learning_rate: 0.001
|
|
optimizer: "adamw"
|
|
loss: "mse"
|
|
early_stopping_patience: 15
|
|
reduce_lr_patience: 5
|
|
reduce_lr_factor: 0.5
|
|
min_lr: 1.0e-7
|
|
gradient_clip: 1.0
|
|
|
|
sequence:
|
|
length: 32
|
|
step: 1
|
|
|
|
mixed_precision:
|
|
enabled: true
|
|
dtype: "bfloat16"
|
|
|
|
# Transformer Settings
|
|
transformer:
|
|
architecture:
|
|
d_model: 512
|
|
nhead: 8
|
|
num_encoder_layers: 4
|
|
num_decoder_layers: 2
|
|
dim_feedforward: 2048
|
|
dropout: 0.1
|
|
use_flash_attention: true
|
|
|
|
training:
|
|
epochs: 100
|
|
batch_size: 512
|
|
learning_rate: 0.0001
|
|
warmup_steps: 4000
|
|
gradient_accumulation_steps: 2
|
|
|
|
sequence:
|
|
max_length: 128
|
|
|
|
# Meta-Model Settings
|
|
meta_model:
|
|
type: "xgboost" # Options: xgboost, linear, ridge, neural
|
|
|
|
xgboost:
|
|
n_estimators: 100
|
|
max_depth: 3
|
|
learning_rate: 0.1
|
|
subsample: 0.8
|
|
colsample_bytree: 0.8
|
|
|
|
neural:
|
|
hidden_layers: [64, 32]
|
|
activation: "relu"
|
|
dropout: 0.2
|
|
|
|
features:
|
|
use_original: true
|
|
use_statistics: true
|
|
max_original_features: 10
|
|
|
|
levels:
|
|
use_level_2: true
|
|
use_level_3: true # Meta-metamodel
|
|
|
|
# AMD Strategy Models
|
|
amd:
|
|
accumulation:
|
|
focus_features: ["volume", "obv", "support_levels", "rsi"]
|
|
model_type: "lstm"
|
|
hidden_size: 64
|
|
|
|
manipulation:
|
|
focus_features: ["volatility", "volume_spikes", "false_breakouts"]
|
|
model_type: "gru"
|
|
hidden_size: 128
|
|
|
|
distribution:
|
|
focus_features: ["momentum", "divergences", "resistance_levels"]
|
|
model_type: "transformer"
|
|
d_model: 256
|
|
|
|
# Output Configuration
|
|
output:
|
|
horizons:
|
|
- name: "scalping"
|
|
id: 0
|
|
range: [1, 6] # 5-30 minutes
|
|
- name: "intraday"
|
|
id: 1
|
|
range: [7, 18] # 35-90 minutes
|
|
- name: "swing"
|
|
id: 2
|
|
range: [19, 36] # 95-180 minutes
|
|
- name: "position"
|
|
id: 3
|
|
range: [37, 72] # 3-6 hours
|
|
|
|
targets:
|
|
- "high"
|
|
- "low"
|
|
- "close"
|
|
- "direction" |