Local Regression: Issues in Higher Dimensions
{"Image DocumentName": "Local Regression: Issues in Higher Dimensions", "Image ImageDescription": "The boundary poses even a greater problem in higher dimensions. Many training points are required to reduce the bias; Sample size should increase exponentially in p to match the same performance. Local regression becomes less useful when dimensions go beyond 2 or 3. It\u2019s impossible to maintain localness (low bias) and sizeable samples (low variance) in the same time.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}