48 You can play with the decision threshold regardless of the balance used in the training set. In other words, techniques like up -or downsampling are orthogonal to this.

Jan 16, 2019 · Pooling and stride both can be used to downsample the image. Let's say we have an image of 4x4, like below and a filter of 2x2. Then how do we decide whether to use (2x2 …

Mar 31, 2022 · I don't think there is a "more right" approach; there are tradeoffs to both. Undersampling in the second approach risks throwing away useful information about the …

Dec 12, 2014 · In this paper Handling class imbalance in customer churn prediction, the authors examine both simple downsampling ("under-sampling") and an "advanced under-sampling …

Jun 17, 2011 · EDIT: With newer drivers, adjusting timings may no longer be necessary in all cases to create down sampling resolutions. Attempt to create a custom resolution using the …

You can either start by downsampling the negative class, so you have a 50:50 ratio of positive to negative sample, and slowly lessen how much you down sample. Or vice versa, start with a …

Jun 9, 2021 · Currently I'm using average pooling for this spatial downsampling, but I'm wondering if there would be an advantage to using max pooling to propagate the highest intensity features.

Sep 22, 2022 · Does downsampling improve accuracy? Because in my experiment with UNet model, 1 original UNet with downsampling and upsampling, and 1 without downsampling …

Mar 1, 2016 · According to the book of Max Kuhn and Kjell Johnson (Applied Predictive Modeling, Springer 2013) class imbalance can be managed by either downsampling the majority class or …

Sep 13, 2024 · Since a single downsampling run may be subject to random variation and introduce biases, I would repeat the downsampling process multiple times (e.g., 𝑘 = 100) to get …