Cai Cai's Machine Learning Sklearn Class: Understandable from Scratch, from Model Invocation to Practical Implementation

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to cleaning ingredients (handling missing values, standardization) Model ...
Benzinga.com

As Tesla Model Y L Orders Cross 120,000 In China, Supply Exhausted Until November

According to the official Tesla China website on Wednesday, deliveries for the Model Y L won't take place until November 2025, indicating that the EV giant has run out of Model Y L units for the rest ...
GitHub

Hugging Face Tokenizer to ONNX Model

This repository demonstrates how to convert Hugging Face tokenizers to ONNX format and use them along with embedding models in multiple programming languages. While we can easily download ONNX models ...
The Lancet

Development and validation of an interpretable multi-task model to predict outcomes in patients with rhabdomyolysis: a multicenter retrospective cohort study

bDepartment of Nephrology, National Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Military Logistics Research Key Laboratory of Field Disease Treatment, ...
ahajournals.org

External Validation of a Risk Prediction Model for Atherosclerotic Cardiovascular Diseases in a Large National Health‐Checkup and Claim Database

The Hisayama risk prediction model for atherosclerotic cardiovascular diseases (ASCVDs) has been featured in the latest Japanese preventive guidelines, yet it lacks external validation. During a ...
Frontiers

Predicting cognitive decline in cognitively impaired patients with ischemic stroke with high risk of cerebral hemorrhage: a machine learning approach

Background and objective: Cognitive decline progresses rapidly in stroke patients, increasing risks of stroke recurrence. Predicting deterioration within a year in patients with poststroke cognitive ...
Frontiers

The impact of cross-validation choices on pBCI classification metrics: lessons for transparent reporting

Neuroadaptive technologies are a type of passive Brain-computer interface (pBCI) that aim to incorporate implicit user-state information into human-machine interactions by monitoring ...
IEEE

Time-Series Classification Using a CNN-LSTM Model with Attention, Autoencoder, and K-Fold Cross-Validation

Abstract: Here, we propose a hybrid Deep Learning (DL) framework consisting of a Denoising Autoencoder (DAE), Convolutional Neural Network (CNN), Bidirectional LSTM (BiLSTM), and a custom Attention ...
ascopubs.org

Impact and validation of the Clavien-Dindo classification for oncologic surgeries in a high-volume center in Latin America: A single-center retrospective study.

Optimizing timeliness of first appointment with medical oncology: A quality improvement initiative at Northwell Health Cancer Institute. Percentage distribution of the Clavien-Dindo risk groups over ...
GitHub

allData allRun vs cross-validation

I am looking at the model projections with "PA=allData, run="allRun", and with "PA = PAx, run=allRun". I found the projections from these two different sets of the model output are quite different.