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feat: add ADX as 24th ML feature for trend strength learning

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Migrate ADX from hard filter (ADX < 25 blocks entry) to ML feature so
the model can learn optimal ADX thresholds from data. Updates FEATURE_COLS,
build_features(), and corresponding tests from 23 to 24 features.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
21in7
2026-03-03 21:11:04 +09:00
parent 038a1f84ec
commit 0b18a0b80d
2 changed files with 10 additions and 7 deletions
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13
tests/test_ml_features.py
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@@ -17,20 +17,21 @@ def _make_df(n=10, base_price=1.0):
"ema21": closes, "ema50": closes, "atr": [0.01] * n,
"stoch_k": [50.0] * n, "stoch_d": [50.0] * n,
"vol_ma20": [1000.0] * n,
"adx": [20.0] * n,
})
def test_build_features_with_btc_eth_has_21_features():
def test_build_features_with_btc_eth_has_24_features():
xrp_df = _make_df(10, base_price=1.0)
btc_df = _make_df(10, base_price=50000.0)
eth_df = _make_df(10, base_price=3000.0)
features = build_features(xrp_df, "LONG", btc_df=btc_df, eth_df=eth_df)
assert len(features) == 23
assert len(features) == 24
def test_build_features_without_btc_eth_has_13_features():
def test_build_features_without_btc_eth_has_16_features():
xrp_df = _make_df(10, base_price=1.0)
features = build_features(xrp_df, "LONG")
assert len(features) == 15
assert len(features) == 16
def test_build_features_btc_ret_1_correct():
xrp_df = _make_df(10, base_price=1.0)
@@ -49,9 +50,9 @@ def test_build_features_rs_zero_when_btc_ret_zero():
features = build_features(xrp_df, "LONG", btc_df=btc_df, eth_df=eth_df)
assert features["xrp_btc_rs"] == 0.0
def test_feature_cols_has_23_items():
def test_feature_cols_has_24_items():
from src.ml_features import FEATURE_COLS
assert len(FEATURE_COLS) == 23
assert len(FEATURE_COLS) == 24
def make_df(n=100):