python分类器实现

说明：  用N来表示训练用例（样本）的个数，M表示特征数目。 输入特征数目m，用于确定决策树上一个节点的决策结果；其中m应远小于M。 从N个训练用例（样本）中以有放回抽样的方式，取样N次，形成一个训练集（即bootstrap取样），并用未抽到的用例（样本）作预测，评估其误差。 对于每一个节点，随机选择m个特征，决策树上每个节点的决定都是基于这些特征确定的。根据这m个特征，计算其最佳的分裂方式。 每棵树都会完整成长而不会剪枝，这有可能在建完一棵正常树状分类器后会被采用）。(N is used to represent the number of training cases (samples), and M is used to represent the number of features. The number of input features m is used to determine the decision result of a node in the decision tree, where m should be far less than m. From N training cases (samples), n times are sampled in the way of put back sampling to form a training set (i.e. bootstrap sampling), and the unselected cases (samples) are used to predict and evaluate the error. For each node, m features are randomly selected, and the decision of each node in the decision tree is determined based on these features. According to these m characteristics, the best splitting mode is calculated. Each tree will grow completely without pruning, which may be adopted after building a normal tree classifier).)

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说明：  0_Linear：线性回归练习 1_LogistRegression：逻辑回归练习 2_boston：波士顿房价预测 3_regularization：正则化 5_stock：股票价格预测 6_CTR：点击率预测 7_all_model：回归与分类模型 8_muticlass：多分类练习 9_regression_implement：不同回归算法tf实现(0_Linear. 1_LogistRegression. 2_boston. 3_regularization. 5_stock. 6_CTR. 7_all_model. 8_muticlass. 9_regression_implement.)

说明：  针对地理学、地理信息系统、遥感技术与应用等专业的技术人员，在使用ArcGIS软件绘图时，可以采用Python 中Arcpy 模块，实现批量处理。 针对栅格数据即遥感影像，在对图像进行分析时，如变化检测，土地覆盖类型提取等。这些都需要依据光谱特征对图像进行分类，并对分类后的结果进行标记。(For the technical personnel of geography, GIS, remote sensing technology and application, arcpy module in Python can be used to realize batch processing when drawing with ArcGIS software. For raster data, that is, remote sensing image, in the analysis of the image, such as change detection, land cover type extraction and so on. All of these need to classify the image according to the spectral characteristics and label the classified results.)

首先对车牌识别系统的现状和已有的技术进行深入的研究，然后开发出一个基于 Python 的车牌识别系统，文中先对车辆图像进行高斯去噪、灰度化和边缘检测等预处理方法，然后用颜色特征和形态特征相结合的方法来确定车牌位置，用彩色分割法来完成车牌分割，最后，运用 SVM 分类训练器完成字符识别并使用Python 软件环境进行车牌识别的仿真实验。(License plate recognition based on SVM)

机器学习算法基于TensorFlow2.0的实现(Implementation of machine learning Based on TensorFlow 2.0)

说明：  機械應力，變形和變形速率之間的關係可能??非常複雜，儘管如果數量足夠小，線性近似在實踐中可能是足夠的。超過材料的某些強度極限的應力將導致永久變形（例如塑性流動，破裂，空化）或甚至改變其晶體結構和化學組成。 在某些工程分支中，術語壓力有時會在寬鬆的意義上用作“內部力量”的同義詞。例如，在桁架的分析中，它可以指作用在樑上的總牽引力或壓縮力，而不是力除以其橫截面的面積。(The relation between mechanical stress, deformation, and the rate of change of deformation can be quite complicated, although a linear approximation may be adequate in practice if the quantities are small enough. Stress that exceeds certain strength limits of the material will result in permanent deformation (such as plastic flow, fracture, cavitation) or even change its crystal structure and chemical composition. In some branches of engineering, the term stress is occasionally used in a looser sense as a synonym of "internal force". For example, in the analysis of trusses, it may refer to the total traction or compression force acting on a beam, rather than the force divided by the area of its cross-section.)

经典书籍，think python,第二版。(think python, second edition. written by Allen B. Downey.)

针对python的congfigparse功能，进行编程，并用实例验证方法的正确性。(The congfigparse for python functions to be programmed, and the correctness of the authentication method with an example.)

说明：  支持向量机 1.理解支持向量机SVM的原理和目标 2.掌握支持向量机的计算过程和算法步骤 3.理解软间隔最大化的含义 4.了解核函数的思想 5.了解SMO算法的过程(Support vector machine 1. Understand the principle and goal of SVM 2. Master the calculation process and algorithm steps of support vector machine 3. Understand the meaning of soft gap maximization 4. Understand the idea of kernel function 5. Understand the process of SMO algorithm)