스킬 aeon
T
시계열 데이터에는 표준 머신러닝을 넘어선 특수 알고리즘이 필요합니다. Aeon은 시간 데이터에 대한 분류, 회귀, 클러스터링, 예측, 이상 탐지, 세분화 및 유사도 검색을 위해 scikit-learn 호환 API를 제공합니다.
지원: Claude Codex Code(CC)
1
스킬 ZIP 다운로드
2
Claude에서 업로드
설정 → 기능 → 스킬 → 스킬 업로드로 이동
3
토글을 켜고 사용 시작
테스트해 보기
"aeon" 사용 중입니다. undefined
예상 결과:
- RocketClassifier 훈련 성공
- 테스트 세트 정확도: 92.3%
- 주요 매개변수: n_kernels=10000
- 데이터 형태 확인: (samples, channels, timepoints)
보안 감사
안전v4 • 1/17/2026
All 531 static findings are false positives. This is a documentation-only skill containing SKILL.md and references/*.md files with no executable code. The scanner incorrectly flagged markdown syntax (backticks for inline code), Python import examples in documentation, ML algorithm names (DTW, LCSS, ERP) misinterpreted as cryptographic references, and legitimate documentation URLs. No actual code execution, network calls, or credential access exists.
14
스캔된 파일
5,466
분석된 줄 수
4
발견 사항
4
총 감사 수
위험 요인
⚡ 스크립트 포함 (8)
evaluation_output.json:33 references/anomaly_detection.md:125-130 references/datasets_benchmarking.md:176-181 references/datasets_benchmarking.md:200-203 references/datasets_benchmarking.md:217-220 references/forecasting.md:111-115 references/segmentation.md:131-134 references/transformations.md:168-172
🌐 네트워크 접근 (6)
⚙️ 외부 명령어 (473)
references/anomaly_detection.md:9 references/anomaly_detection.md:13 references/anomaly_detection.md:25 references/anomaly_detection.md:29 references/anomaly_detection.md:33 references/anomaly_detection.md:37 references/anomaly_detection.md:41 references/anomaly_detection.md:45 references/anomaly_detection.md:49 references/anomaly_detection.md:57 references/anomaly_detection.md:61 references/anomaly_detection.md:69 references/anomaly_detection.md:73 references/anomaly_detection.md:77 references/anomaly_detection.md:83 references/anomaly_detection.md:89-107 references/anomaly_detection.md:107-124 references/anomaly_detection.md:124-136 references/classification.md:9 references/classification.md:10 references/classification.md:11 references/classification.md:12 references/classification.md:13 references/classification.md:21 references/classification.md:22 references/classification.md:23 references/classification.md:24 references/classification.md:25 references/classification.md:26 references/classification.md:27 references/classification.md:35 references/classification.md:36 references/classification.md:37 references/classification.md:38 references/classification.md:46 references/classification.md:47 references/classification.md:48 references/classification.md:56 references/classification.md:57 references/classification.md:58 references/classification.md:59 references/classification.md:60 references/classification.md:68 references/classification.md:69 references/classification.md:70 references/classification.md:71 references/classification.md:72 references/classification.md:73 references/classification.md:81 references/classification.md:82 references/classification.md:83 references/classification.md:84 references/classification.md:92 references/classification.md:93 references/classification.md:101 references/classification.md:102 references/classification.md:110 references/classification.md:118 references/classification.md:119 references/classification.md:120 references/classification.md:124-136 references/clustering.md:9 references/clustering.md:10 references/clustering.md:11 references/clustering.md:12 references/clustering.md:20 references/clustering.md:21 references/clustering.md:29 references/clustering.md:30 references/clustering.md:38 references/clustering.md:46 references/clustering.md:47 references/clustering.md:48 references/clustering.md:49 references/clustering.md:50 references/clustering.md:51 references/clustering.md:59 references/clustering.md:60 references/clustering.md:61 references/clustering.md:69 references/clustering.md:75 references/clustering.md:76 references/clustering.md:77 references/clustering.md:78 references/clustering.md:84-99 references/datasets_benchmarking.md:10-19 references/datasets_benchmarking.md:19-22 references/datasets_benchmarking.md:22-31 references/datasets_benchmarking.md:31-34 references/datasets_benchmarking.md:34-39 references/datasets_benchmarking.md:39-42 references/datasets_benchmarking.md:42-46 references/datasets_benchmarking.md:46-51 references/datasets_benchmarking.md:51-55 references/datasets_benchmarking.md:55-58 references/datasets_benchmarking.md:58-62 references/datasets_benchmarking.md:62-65 references/datasets_benchmarking.md:65-69 references/datasets_benchmarking.md:69-72 references/datasets_benchmarking.md:72-76 references/datasets_benchmarking.md:76-79 references/datasets_benchmarking.md:79-83 references/datasets_benchmarking.md:83-88 references/datasets_benchmarking.md:88-92 references/datasets_benchmarking.md:92-95 references/datasets_benchmarking.md:95-99 references/datasets_benchmarking.md:99-106 references/datasets_benchmarking.md:106-107 references/datasets_benchmarking.md:107-108 references/datasets_benchmarking.md:108-109 references/datasets_benchmarking.md:109-113 references/datasets_benchmarking.md:113-122 references/datasets_benchmarking.md:122-128 references/datasets_benchmarking.md:128-134 references/datasets_benchmarking.md:134-142 references/datasets_benchmarking.md:142-153 references/datasets_benchmarking.md:153-159 references/datasets_benchmarking.md:159-168 references/datasets_benchmarking.md:168-175 references/datasets_benchmarking.md:175-188 references/datasets_benchmarking.md:188-191 references/datasets_benchmarking.md:191-196 references/datasets_benchmarking.md:196-199 references/datasets_benchmarking.md:199-210 references/datasets_benchmarking.md:210-216 references/datasets_benchmarking.md:216-227 references/datasets_benchmarking.md:227-235 references/datasets_benchmarking.md:235-240 references/datasets_benchmarking.md:240-244 references/datasets_benchmarking.md:244-247 references/datasets_benchmarking.md:247-261 references/datasets_benchmarking.md:261-285 references/datasets_benchmarking.md:285-293 references/datasets_benchmarking.md:293-301 references/datasets_benchmarking.md:301-307 references/datasets_benchmarking.md:307-310 references/datasets_benchmarking.md:310-316 references/datasets_benchmarking.md:316-322 references/datasets_benchmarking.md:322-328 references/datasets_benchmarking.md:328-337 references/datasets_benchmarking.md:337-343 references/datasets_benchmarking.md:343-353 references/datasets_benchmarking.md:353-359 references/datasets_benchmarking.md:359-369 references/datasets_benchmarking.md:369-375 references/datasets_benchmarking.md:375-387 references/distances.md:12 references/distances.md:13 references/distances.md:14 references/distances.md:15 references/distances.md:16 references/distances.md:19 references/distances.md:20 references/distances.md:21 references/distances.md:22 references/distances.md:25 references/distances.md:26 references/distances.md:27 references/distances.md:35 references/distances.md:36 references/distances.md:37 references/distances.md:38 references/distances.md:46-54 references/distances.md:54-58 references/distances.md:58-67 references/distances.md:67-71 references/distances.md:71-80 references/distances.md:80-84 references/distances.md:84-94 references/distances.md:94-102 references/distances.md:102-108 references/distances.md:108-114 references/distances.md:114-117 references/distances.md:117-121 references/distances.md:121-130 references/distances.md:130-169 references/distances.md:169-174 references/distances.md:174-180 references/distances.md:180-183 references/distances.md:183-194 references/distances.md:194-197 references/distances.md:197-208 references/distances.md:208-220 references/distances.md:220-226 references/distances.md:226-236 references/distances.md:236-242 references/distances.md:242-247 references/distances.md:247-251 references/distances.md:251-256 references/forecasting.md:9 references/forecasting.md:10 references/forecasting.md:10 references/forecasting.md:18 references/forecasting.md:19 references/forecasting.md:19 references/forecasting.md:19 references/forecasting.md:23 references/forecasting.md:24 references/forecasting.md:24 references/forecasting.md:24 references/forecasting.md:28 references/forecasting.md:29 references/forecasting.md:33 references/forecasting.md:34 references/forecasting.md:34 references/forecasting.md:38 references/forecasting.md:45 references/forecasting.md:49 references/forecasting.md:57 references/forecasting.md:58 references/forecasting.md:58 references/forecasting.md:63-80 references/forecasting.md:80-84 references/forecasting.md:84-86 references/forecasting.md:86-93 references/forecasting.md:93-110 references/forecasting.md:110-121 references/forecasting.md:121-127 references/forecasting.md:127-133 references/forecasting.md:133-137 references/forecasting.md:137-138 references/networks.md:107-123 references/networks.md:123-129 references/networks.md:129-138 references/networks.md:138-142 references/networks.md:142-143 references/networks.md:143-144 references/networks.md:144-145 references/networks.md:145-155 references/networks.md:155-156 references/networks.md:156-157 references/networks.md:157-164 references/networks.md:164-174 references/networks.md:174-180 references/networks.md:180-187 references/networks.md:187-219 references/networks.md:219-225 references/networks.md:225-231 references/networks.md:231-240 references/networks.md:240-254 references/networks.md:254-266 references/networks.md:266-280 references/networks.md:280-289 references/regression.md:9 references/regression.md:10 references/regression.md:11 references/regression.md:12 references/regression.md:13 references/regression.md:21 references/regression.md:22 references/regression.md:23 references/regression.md:24 references/regression.md:25 references/regression.md:26 references/regression.md:27 references/regression.md:28 references/regression.md:29 references/regression.md:37 references/regression.md:45 references/regression.md:46 references/regression.md:47 references/regression.md:48 references/regression.md:56 references/regression.md:64 references/regression.md:65 references/regression.md:66 references/regression.md:67 references/regression.md:68 references/regression.md:69 references/regression.md:77 references/regression.md:85 references/regression.md:86 references/regression.md:87 references/regression.md:91 references/regression.md:92 references/regression.md:93 references/regression.md:97-109 references/segmentation.md:8 references/segmentation.md:10 references/segmentation.md:10 references/segmentation.md:14 references/segmentation.md:20 references/segmentation.md:26 references/segmentation.md:31 references/segmentation.md:37 references/segmentation.md:42 references/segmentation.md:47 references/segmentation.md:52 references/segmentation.md:57-73 references/segmentation.md:73-79 references/segmentation.md:79-82 references/segmentation.md:82-99 references/segmentation.md:99-104 references/segmentation.md:104-109 references/segmentation.md:109-114 references/segmentation.md:114-119 references/segmentation.md:119-124 references/segmentation.md:124-130 references/segmentation.md:130-141 references/segmentation.md:141-154 references/segmentation.md:154-163 references/similarity_search.md:10 references/similarity_search.md:16 references/similarity_search.md:22 references/similarity_search.md:31 references/similarity_search.md:38-58 references/similarity_search.md:58-62 references/similarity_search.md:62-79 references/similarity_search.md:79-83 references/similarity_search.md:83-97 references/similarity_search.md:97-108 references/similarity_search.md:108-121 references/similarity_search.md:121-136 references/similarity_search.md:136-141 references/similarity_search.md:141-146 references/similarity_search.md:146-150 references/similarity_search.md:150-155 references/similarity_search.md:155-162 references/transformations.md:17 references/transformations.md:18 references/transformations.md:19 references/transformations.md:20 references/transformations.md:21 references/transformations.md:22 references/transformations.md:30 references/transformations.md:31 references/transformations.md:32 references/transformations.md:33 references/transformations.md:41 references/transformations.md:42 references/transformations.md:43 references/transformations.md:44 references/transformations.md:45 references/transformations.md:46 references/transformations.md:54 references/transformations.md:55 references/transformations.md:56 references/transformations.md:57 references/transformations.md:65 references/transformations.md:66 references/transformations.md:67 references/transformations.md:75 references/transformations.md:76 references/transformations.md:77 references/transformations.md:78 references/transformations.md:79 references/transformations.md:80 references/transformations.md:88 references/transformations.md:89 references/transformations.md:90 references/transformations.md:91 references/transformations.md:92 references/transformations.md:93 references/transformations.md:97 references/transformations.md:98 references/transformations.md:99 references/transformations.md:105 references/transformations.md:113 references/transformations.md:114 references/transformations.md:115 references/transformations.md:119 references/transformations.md:120 references/transformations.md:121 references/transformations.md:122 references/transformations.md:123 references/transformations.md:124 references/transformations.md:130 references/transformations.md:131 references/transformations.md:135 references/transformations.md:136 references/transformations.md:137 references/transformations.md:141 references/transformations.md:145-163 references/transformations.md:163-167 references/transformations.md:167-181 references/transformations.md:181-185 references/transformations.md:185-191 references/transformations.md:191-216 references/transformations.md:216-220 references/transformations.md:220-223 references/transformations.md:223-229 references/transformations.md:229-232 references/transformations.md:232-236 SKILL.md:28-30 SKILL.md:30-36 SKILL.md:36-39 SKILL.md:39-51 SKILL.md:51-54 SKILL.md:54 SKILL.md:54-55 SKILL.md:55 SKILL.md:55-56 SKILL.md:56 SKILL.md:56-57 SKILL.md:57-61 SKILL.md:61-64 SKILL.md:64-74 SKILL.md:74-78 SKILL.md:78-81 SKILL.md:81-91 SKILL.md:91-95 SKILL.md:95-98 SKILL.md:98-104 SKILL.md:104-108 SKILL.md:108-111 SKILL.md:111-120 SKILL.md:120-124 SKILL.md:124-127 SKILL.md:127-132 SKILL.md:132-136 SKILL.md:136-139 SKILL.md:139-145 SKILL.md:145-149 SKILL.md:149-152 SKILL.md:152-162 SKILL.md:162-165 SKILL.md:165-170 SKILL.md:170-173 SKILL.md:173-178 SKILL.md:178-182 SKILL.md:182-185 SKILL.md:185-202 SKILL.md:202-211 SKILL.md:211-214 SKILL.md:214 SKILL.md:214 SKILL.md:214-215 SKILL.md:215 SKILL.md:215-216 SKILL.md:216 SKILL.md:216-219 SKILL.md:219-225 SKILL.md:225-229 SKILL.md:229-232 SKILL.md:232-240 SKILL.md:240-243 SKILL.md:243-248 SKILL.md:248-254 SKILL.md:254-266 SKILL.md:266-270 SKILL.md:270-283 SKILL.md:283-287 SKILL.md:287-301 SKILL.md:301-308 SKILL.md:308-313 SKILL.md:313-316 SKILL.md:316-320 SKILL.md:320-322 SKILL.md:322-334 SKILL.md:334-335 SKILL.md:335-336 SKILL.md:336-339 SKILL.md:339 SKILL.md:339-340 SKILL.md:340-341 SKILL.md:341 SKILL.md:341-344 SKILL.md:344 SKILL.md:344-345 SKILL.md:345 SKILL.md:345-348 SKILL.md:348-353 SKILL.md:353-354 SKILL.md:354-355 SKILL.md:355-356 SKILL.md:356-357 SKILL.md:357-358 SKILL.md:358-359 SKILL.md:359-360 SKILL.md:360-361 SKILL.md:361-362 SKILL.md:362-363 SKILL.md:363-364
🔑 환경 변수 (1)
감사자: claude 감사 이력 보기 →
품질 점수
45
아키텍처
100
유지보수성
83
콘텐츠
20
커뮤니티
100
보안
91
사양 준수
만들 수 있는 것
예측 모델 구축
특수 시계열 알고리즘으로 센서 판독 분류, 장비 고장 예측 또는 판매 추세 예측
시간 패턴 분석
생리학적 신호에서 이상 탐지,基因组 데이터 세분화 또는 실험 시퀀스에서 반복 모티프 찾기
시계열 파이프라인 확장
sklearn 파이프라인과 통합, 벤치마크 결과 비교 및 프로덕션 준비된 시계열 모델 배포
이 프롬프트를 사용해 보세요
기본 분류
X_train, y_train의 시계열 데이터를 aeon으로 분류 RocketClassifier를 훈련하고 X_test에서 정확도를 평가하세요
이상 탐지
나의 시계열 y에서 aeon을 사용하여 이상 탐지 window_size=50인 STOMP 탐지기를 사용하고 anomaly_scores가 95번째 백분위수를 초과하는 인덱스를 반환하세요
예측
훈련 데이터에 ARIMA 예측기(order=(1,1,1))를 훈련하고 다음 5개 값을 예측하세요
파이프라인 최적화
Normalizer, RocketTransformer 및 GradientBoostingClassifier를 사용하여 sklearn 파이프라인을 생성하세요 aeon 변환기와 sklearn 추정기 사용
모범 사례
- aeon.transformations.collection.Normalizer를 사용하여 대부분의 알고리즘을 적용하기 전에 시계열 데이터 정규화
- 딥러닝 방법을 시도하기 전에 빠른 프로토타이핑을 위해 MiniRocketClassifier 또는 RocketClassifier로 시작
- 교차 검증을 사용하고 1-NN Euclidean과 같은 기준선 방법과 비교하여 모델 성능 검증
피하기
- 100개 미만의 샘플이 있는 소규모 데이터 세트에서 딥러닝 분류기 사용
- DTW 또는 기타 탄성 거리 측정값으로 작업할 때 데이터 정규화 건너뛰기
- 필요한 입력 형태(n_samples, n_channels, n_timepoints) 무시
자주 묻는 질문
aeon의 입력 형식은 무엇입니까?
Aeon은 (n_samples, n_channels, n_timepoints) 형태의 시계열을 예상합니다. 단변량 데이터는 n_channels=1이어야 합니다.
어떤 분류기가 가장 빠릅니까?
MiniRocketClassifier가 최고의 속도-성능 균형을 제공합니다. RocketClassifier도 더 많은 커널로 빠릅니다.
sklearn 파이프라인을 사용할 수 있습니까?
네, aeon 변환기와 분류기는 sklearn Pipeline 및 GridSearchCV와 완전히 호환됩니다.
이상을 어떻게 탐지합니까?
aeon.anomaly_detection의 STOMP 또는 LeftSTAMP를 사용하세요. 이상 점수를 얻으려면 fit_predict를 호출하세요.
어떤 거리 측정값이 사용 가능합니까?
DTW, DDTW, WDTW, Euclidean, Manhattan, LCSS, ERP, EDR, TWE, MSM 및 Shape-DTW.
결측값을 어떻게 처리합니까?
분류기나 예측기를 적용하기 전에 aeon.transformations.collection의 SimpleImputer를 사용하세요.