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相关概念视频

Force Classification01:22

Force Classification

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Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
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Machines: Problem Solving II01:30

Machines: Problem Solving II

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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Mass Analyzers: Common Types01:19

Mass Analyzers: Common Types

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The quadrupole mass analyzer consists of four cylindrical metal rods arranged in a diamond carrying a DC voltage and a radio-frequency AC voltage. The motion of ions through the quadrupole depends on the field strength, causing only ions of a certain m/z to resonate successfully and strike the detector at a given field strength. Though the transmission rate for these analyzers is high, the exact elemental composition of the sample is not determined because of low resolution; however, they are...
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Machines: Problem Solving I01:22

Machines: Problem Solving I

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A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
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Classification of Systems-I01:26

Classification of Systems-I

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Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
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Mass Analyzers: Overview01:13

Mass Analyzers: Overview

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The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...
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使用简单的低代码机器学习来识别POP.

Lei Xin1, Haiying Yu2, Sisi Liu1

  • 1School of Environment, MOE Key Laboratory of Theoretical Chemistry of Environment, South China Normal University, Guangzhou 510006, China; Environmental Research Institute, Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety, South China Normal University, Guangzhou 510006, China.

The Science of the total environment
|February 22, 2024
PubMed
概括
此摘要是机器生成的。

使用PyCaret构建的机器学习模型有效地使用最小代码选持久有机污染物 (POP). 这些可访问的工具优于复杂的深度学习模型,帮助环境科学家在化学物质管理中发挥作用.

关键词:
化学品管理 化学品管理分类 分类 分类 分类.机器学习是机器学习.持久性有机污染物 (POP) 是一种持续性有机污染物.这就是PyCaret的PyCaret.风险评估 风险评估 风险评估

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科学领域:

  • 环境化学环境化学
  • 计算化学计算化学
  • 毒理学 毒理学 毒理学

背景情况:

  • 从大型化学数据集中识别持久有机污染物 (POP) 是一个挑战.
  • 现有的机器学习模型通常需要先进的编程和计算资源.
  • 需要可访问的工具来进行有效的POP查.

研究的目的:

  • 使用PyCaret包开发和评估用于POP查的机器学习模型.
  • 将PyCaret模型的性能与深度卷积神经网络 (DCNN) 的性能进行比较.
  • 评估低代码机器学习对环境科学应用的有用性.

主要方法:

  • 使用PyCaret,一个Python包,用于构建机器学习模型.
  • 采用2D分子描述器用于POP识别.
  • 与DCNN比较了几个PyCaret模型,包括光梯度增强机 (LGBM),与DCNN相比.

主要成果:

  • 在PyCaret模型中,比DCNN的性能更好或相似.
  • 在LGBM模型中,高精度 (96.20%),AUC (97.70%) 和F1得分 (82.58%).
  • 根据LGBM模型,在REACH PBT和工业化学品清单中有效地识别了POP.

结论:

  • PyCaret提供了一种简单,易于使用的方法来构建有效的POP查模型.
  • 像PyCaret这样的低代码机器学习工具使非计算专业人员在环境科学中获得权力.
  • 这些工具有助于快速评估和管理化学物质.