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    1612877985

    展开全文
  • 分类是一种常见的机器学习算法,是一种有监督的算法。简单说就是给出学习集数据都是带标签的,通过训练学习集数据获得模型,对未来给出的实际数据,根据模型进行分类。这里采用K最近邻算法(KNN,K-nearest ...

    分类是一种常见的机器学习算法,是一种有监督的算法。简单说就是给出学习集数据都是带标签的,通过训练学习集数据获得模型,对未来给出的实际数据,根据模型进行分类。这里采用K最近邻算法(KNN,K-nearest neighbour)

    KNN算法非常直观,容易理解,就是寻找K个距离最近的邻居,看这K个近邻中哪个分类标签多,样本就归于哪类。

    下面以一个对学生文理、综合分类问题进行实例操作。

    数据文件是一个学生成绩及分类表,样式如下

    ID yingyu yuwen shuxue ClassifyResult

    0 0 80 80 79 3

    1 1 99 89 60 1

    2 2 60 78 90 2

    3 3 90 70 88 3

    4 4 66 77 88 2

    代码如下:

    import pandas as pd

    from sklearn import neighbors

    df = pd.read_csv('student.csv')

    train_x = df.iloc[0:80,2:4] # 取数据集前80条记录的语文,数学成绩作为训练集输入

    train_y = df.iloc[0:80, 4] # 取数据集前80条记录的标签值,即分类值作为训练集的输出

    model = neighbors.KNeighborsClassifier() # 创建最近邻模型

    model.fit(train_x, train_y) # 指定输入输出,创建模型

    test_x = df.iloc[80:100, 2:4]# 取测试集输入

    test_y = df.iloc[80:100, 4].values #取测试集输出,并将数据框转换成数组

    test_p = model.predict(test_x)

    print(test_p)

    print(test_y)

    rate = model.score(test_x,test_y) # 记算预测结果的正确率

    print('预测结果的正确率是{0:*^10}'.format(rate))

    运行结果如下:

    [3 1 1 3 3 3 1 1 3 2 2 3 1 3 1 3 3 3 3 1]

    [2 3 3 3 3 3 1 1 2 2 2 3 1 3 1 3 1 1 3 3]

    预测结果的正确率是***0.65***

    此次预测的正确率为0.65,并不是很高,主要是输入训练文件质量不高造成的。但这个小程序实现了KNN分类算法的全部功能,还是值得借鉴的

    展开全文
  • 如果尚未安装python库,你需要安装以下python库:opencv-pythoncvlibmatplotlibtensorflow下面的代码导入所需的python库,从存储中读取图像,对图像执行目标检测,并显示带有边界框和关于检测目标的标签的图像。...

    15a19e331165606192f0d08b063ac702.png

    要知道图像中的目标是什么?

    或者你想数一幅图里有多少个苹果?

    在本文中,我将向你展示如何使用Python在不到10行代码中创建自己的目标检测程序。

    如果尚未安装python库,你需要安装以下python库:

    opencv-python

    cvlib

    matplotlib

    tensorflow

    下面的代码导入所需的python库,从存储中读取图像,对图像执行目标检测,并显示带有边界框和关于检测目标的标签的图像。

    import cv2

    import matplotlib.pyplot as plt

    import cvlib as cv

    from cvlib.object_detection import draw_bbox

    im = cv2.imread('apple-256261_640.jpg')

    bbox, label, conf = cv.detect_common_objects(im)

    output_image = draw_bbox(im, bbox, label, conf)

    plt.imshow(output_image)

    plt.show()

    下面是使用上述代码进行目标检测的一些结果。

    1989c1a8876ad41551cf3af5c2ee7bf1.png

    bd01b83628f762e22d088d2055972448.png

    400ae7fc1e7663ca5d8fc8cd146fde49.png

    到这,你就已经准备完成你的目标检测程序了。

    要了解更多关于cvlib库的信息,可以访问下面的链接。

    cvlib[^1]

    以下是一些进一步的阅读资料,以了解目标检测的工作原理:

    使用深度学习方法的目标检测[^2]

    基本目标检测算法的逐步介绍(第1部分)[^3]

    [^1]: https://www.cvlib.net/[^2]: https://towardsdatascience.com/object-detection-using-deep-learning-approaches-an-end-to-end-theoretical-perspective-4ca27eee8a9a[^3]: https://www.analyticsvidhya.com/blog/2018/10/a-step-by-step-introduction-to-the-basic-object-detection-algorithms-part-1/

    欢迎关注磐创博客资源汇总站:http://docs.panchuang.net/

    欢迎关注PyTorch官方中文教程站:http://pytorch.panchuang.net/

    展开全文
  • 资源分享:超牛人工智能项目课-带全套源码 基于Python深度有趣 多项目实战人工智能学习教程 课程目录: PYTHON 深度有趣 多项目实战课程 云计算吧 人工智能 网易云课堂 (0);目录中文...资源分享:超牛人工智能项目...

    资源分享:超牛人工智能项目课-带全套源码 基于Python深度有趣 多项目实战人工智能学习教程 课程目录: PYTHON 深度有趣 多项目实战课程 云计算吧 人工智能 网易云课堂 (0);目录中文...

    资源分享:超牛人工智能项目课-带全套源码 基于Python深度有趣 多项目实战人工智能学习教程

    404f12fe3d32cf3e86320281d36b8cc6.png

    课程目录:

    PYTHON 深度有趣 多项目实战课程   云计算吧  人工智能  网易云课堂

    (0);目录中文件数:32个

    ├─(1) 00 文档.swf

    ├─(2) 01 前言.mp4

    ├─(3) 02 准备工作.mp4

    ├─(4) 03 高端又一般的词云.mp4

    ├─(5) 04 图像风格迁移.mp4

    ├─(6) 05 自编码器图像去噪.mp4

    ├─(7) 06 变分自编码器.mp4

    ├─(8) 07 生成式对抗网络-1.mp4

    ├─(9) 07 生成式对抗网络-2.mp4

    ├─(10) 08 DCgan人脸图片生成.mp4

    ├─(11) 09 Inception-v3图片分类.mp4

    ├─(12) 10 股票价格预测.mp4

    ├─(13) 11 TensorFlow物体检测.mp4

    ├─(14) 12 一起来动动手.mp4

    ├─(15) 13 词向量的训练.mp4

    ├─(16) 14 Dlib快速入门.mp4

    ├─(17) 15 浅谈中文分词.mp4

    ├─(18) 16 令人拍案叫绝的WGAN.mp4

    ├─(19) 17 CGAN和ACGAN.mp4

    ├─(20) 18 二次元头像生成.mp4

    ├─(21) 19 pix2pix图像翻译.mp4

    ├─(22) 20 CycleGAN性别转换.mp4

    ├─(23) 21 从FlappyBird到DQN.mp4

    ├─(24) 22 天马星空的Deepdream.mp4

    ├─(25) 23 歌词古诗自动生成.mp4

    ├─(26) 24 语句相似度计算.mp4

    ├─(27) 25 图像标题生成.mp4

    ├─(28) 26 Seq2Seq机器翻.mp4

    ├─(29) 27 服饰关键点定位.mp4

    ├─(30) 28 自动语音识别.mp4

    ├─(31) 29 方言种类分类.mp4

    ├─(32) 30 快速图像风格迁移.mp4

    (1)代码;目录中文件数:0个

    (2)代码完整版;目录中文件数:28个

    ├─(33) 03 词云.zip

    ├─(34) 04 图像风格迁移.zip

    ├─(35) 05 自编码器图像去噪.zip

    ├─(36) 06 变分自编码器.zip

    ├─(37) 07 生成式对抗网络.zip

    ├─(38) 08 DCGAN人脸图片生成.zip

    ├─(39) 09 Inception-v3图片分类.zip

    ├─(40) 10 股票价格预测.zip

    ├─(41) 11 TensorFlow物体检测.zip

    ├─(42) 12 一起来动动手.zip

    ├─(43) 13 词向量的训练.zip

    ├─(44) 14 dlib快速入门.zip

    ├─(45) 15 浅谈中文分词.zip

    ├─(46) 16 令人拍案叫绝的WGAN.zip

    ├─(47) 17 CGAN和ACGAN.zip

    ├─(48) 18 二次元头像生成.zip

    ├─(49) 19 pix2pix图像翻译.zip

    ├─(50) 20 CycleGAN性别转换.zip

    ├─(51) 21 从FlappyBird到DQN.zip

    ├─(52) 22 天马星空的DeepDream.zip

    ├─(53) 23 歌词古诗自动生成.zip

    ├─(54) 24 语句相似度计算.zip

    ├─(55) 25 图像标题生成.zip

    ├─(56) 26 Seq2Seq机器翻译.zip

    ├─(57) 27 服饰关键点定位.zip

    ├─(58) 28 自动语音识别.zip

    ├─(59) 29 方言种类分类.zip

    ├─(60) 30 快速图像风格迁移.zip

    (3)代码精简版;目录中文件数:28个

    ├─(61) 03 词云.zip

    ├─(62) 04 图像风格迁移.zip

    ├─(63) 05 自编码器图像去噪.zip

    ├─(64) 06 变分自编码器.zip

    ├─(65) 07 生成式对抗网络.zip

    ├─(66) 08 DCGAN人脸图片生成.zip

    ├─(67) 09 Inception-v3图片分类.zip

    ├─(68) 10 股票价格预测.zip

    ├─(69) 11 TensorFlow物体检测.zip

    ├─(70) 12 一起来动动手.zip

    ├─(71) 13 词向量的训练.zip

    ├─(72) 14 dlib快速入门.zip

    ├─(73) 15 浅谈中文分词.zip

    ├─(74) 16 令人拍案叫绝的WGAN.zip

    ├─(75) 17 CGAN和ACGAN.zip

    ├─(76) 18 二次元头像生成.zip

    ├─(77) 19 pix2pix图像翻译.zip

    ├─(78) 20 CycleGAN性别转换.zip

    ├─(79) 21 从FlappyBird到DQN.zip

    ├─(80) 22 天马星空的DeepDream.zip

    ├─(81) 23 歌词古诗自动生成.zip

    ├─(82) 24 语句相似度计算.zip

    ├─(83) 25 图像标题生成.zip

    ├─(84) 26 Seq2Seq机器翻译.zip

    ├─(85) 27 服饰关键点定位.zip

    ├─(86) 28 自动语音识别.zip

    ├─(87) 29 方言种类分类.zip

    ├─(88) 30 快速图像风格迁移.zip

    资源下载信息:

    全栈记事资源分享交流④群:906625830

    全栈记事资源分享交流④群:906625830

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