3 个仓库
Awesome GitHub RepositoriesNative Missing Value Handlers
Accepts numerical, categorical, and missing values directly without preprocessing, cleaning, or imputation steps.
Distinct from Missing Data Imputation: Distinct from Missing Data Imputation: does not fill missing values; instead processes them natively without any imputation step.
Explore 3 awesome GitHub repositories matching data & databases · Native Missing Value Handlers. Refine with filters or upvote what's useful.
Awesome Native Missing Value Handlers GitHub Repositories
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- priorlabs/tabpfn
PriorLabs/TabPFN
7,408在 GitHub 上查看Handles missing values natively in raw tabular input without requiring any preprocessing or imputation.
Pythondata-sciencefoundation-modelsmachine-learning - nixtla/neuralforecast
Nixtla/neuralforecast
4,160在 GitHub 上查看Neuralforecast 是一个神经时间序列预测库，旨在利用深度学习架构预测一个或多个序列的未来值。它是一个分布式机器学习预测框架，支持跨多个时间序列训练全局模型，通过交叉学习提高泛化能力。 该项目作为一个概率预测工具包，能够生成不确定性区间和概率分布，而不仅仅是单一的点估计。它还包含一个分层预测协调器，以确保不同组织或地理层级的预测结果与其汇总总数保持一致。 该库涵盖了广泛的功能，包括外生变量集成、自动超参数优化和迁移学习。它提供了通过交叉验证和滑动窗口技术进行模型验证的工具，以及利用 Spark 在计算集群上分发训练任务的能力。 该系统支持通过云存储集成实现模型持久化，并提供了对趋势和季节性等预测组件的解释机制。
Processes datasets with unobserved entries natively using mask columns without requiring prior imputation.
Python - xtensor-stack/xtensor
xtensor-stack/xtensor
3,748在 GitHub 上查看xtensor is a C++ multidimensional array library for numerical computing that provides N-dimensional containers with an interface mirroring the NumPy API. It utilizes a lazy evaluation expression engine to defer numerical computations until assignment, which minimizes memory allocations and intermediate copies. The library features a foreign memory array adaptor that allows it to wrap external buffers, such as NumPy arrays, to perform numerical operations in-place without duplicating data. It further optimizes performance through lazy broadcasting and a system that manages the lifetime of temp
Deno-xtensor manages arrays with invalid entries using optional value types to maintain integrity.
C++c-plus-plus-14multidimensional-arraysnumpy
