그래프를 사용하면 데이터에 숨겨진 이상치나 패턴을 찾을 수 있습니다.
따라서 분석을 진행하기 전에 산점도 또는 히스토그램으로 데이터를 그래픽으로 살펴보세요. 데이터 파이프라인 시작 시뿐만 아니라 데이터 변환 전반에서 그래프를 볼 수 있습니다. 시각화를 사용하면 가정을 지속적으로 확인할 수 있습니다.
[null,null,["최종 업데이트: 2025-01-30(UTC)"],[[["Before creating feature vectors, it is crucial to analyze numerical data by visualizing it through plots and graphs and calculating basic statistics like mean, median, and standard deviation."],["Visualizations, such as scatter plots and histograms, can reveal anomalies and patterns in the data, aiding in identifying potential issues early in the data analysis process."],["Outliers, values significantly distant from others, should be identified and handled appropriately, either by correcting mistakes, retaining legitimate outliers for model training, or applying techniques like clipping."],["Statistical evaluation helps in understanding the distribution and characteristics of data, providing insights into potential feature and label relationships."],["While basic statistics and visualizations provide valuable insights, it's essential to remain vigilant as anomalies can still exist in seemingly well-balanced data."]]],[]]
