From 80eefd1667b102a9d48230197f0089b3a0e9dca2 Mon Sep 17 00:00:00 2001 From: Thieu Nguyen Date: Mon, 25 Sep 2023 10:20:12 +0700 Subject: [PATCH] Udpate readme --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 2c7ea51..7686efc 100644 --- a/README.md +++ b/README.md @@ -299,8 +299,8 @@ data = Data(X, y) data.split_train_test(test_size=0.2, random_state=10) # Try different random_state value ``` -3) When testing several algorithms based on Extreme Learning Machines (ELM), they all produce the same results. - Even during the training process, the global best solution remains unchanged. +3) **When testing several algorithms based on Extreme Learning Machines (ELM), they all produce the same results. + Even during the training process, the global best solution remains unchanged.** + This issue was identified in version <= v1.0.2 when the default values for the lower bound (lb) and upper bound (ub) were set in the narrow range of (-1, 1). This limited range proved to be too small, causing all algorithms to converge to local optima. Fortunately, this problem has been addressed in versions > v1.0.3, where the default