# homework作业 | Machine Learning | report – Machine Learning

### Machine Learning

homework作业 | report – 这是一个Machine Learning的practice, 考察k-mean算法的理解, 是比较有代表性的机器学习等代写方向, 这是值得参考的homework代写的题目

``````My sites/ 21S-STATS413-80/ Homeworks/  homework 05 --- Boosting & Clustering Spring^2021 - Week 8
``````
``````Spring 2021 - STATS413-80 - WU
``````

### Machine Learning

#### Homework 05 – — Boosting & Clustering

Clustering Try K-mean and spectral clustering on toy dataset. Follow Tutorial: It use sklearn (install it by pip install scikit-learn) package to perform k-means.

#### Detailed requirement

``````1. As usual, write introduction, key equations, and kernel functions.
2. Read and play the tutorial. Use the following code to produce the toy data.
np.random.seed(1)
``````

def xy(eta, n): theta = np.random.uniform(0, 2 * np.pi, n) (^) x = eta * np.cos(theta) + np.random.normal(0, 0.05, n) y = eta * np.sin(theta) + np.random.normal(0, 0.05, n) return x, y (^) x0, y0 = xy(0.1, 50) x1, y1 = xy(1.0, 200) x2, y2 = xy(2.0, 400) x = np.concatenate((x0, x1, x2), axis=0) (^) y = np.concatenate((y0, y1, y2), axis=0) X = np.transpose(np.vstack((x, y))) That should looks like this:

1. Use gaussian kernel in computing similarity matrix. Change delta in the gaussian kernel to {0.1, 0.2, 0.5, 1}. See SpectralClustering — Notes section and Attributes: affinity_matrix_. Print the similarity matrix for each delta. (n*n grid, darker as higher value, brighter as lower value). You may use plt.matshow(). See example: Discuss how delta affect the similarity matrix.
2. Train 5 clustering, k-means, spectral clustering with delta {0.1, 0.2, 0.5, 1}. For each of them, visualize the clustering results like the last two images in tutorial. Meanwhile, compare the accuracy for these 5 methods.

#### Grading (total 100 pts)

``````Homework  report (90pts)
``````
``````Get the mobile app
``````
``````Clustering (90pts)
introduction: 5pts
main equation, structures, equations: 30pts
Similarity matrix graph: 20pts (5pts for each)
Result visualization: 25pts (5 for each)
Accuracy comparison: 10pts
Submit the code (py or ipynb): 10pts
``````

#### Submission status

``````Submission status No attempt
Due date Sunday, 30 May 2021, 11:59 PM PDT
Time remaining 10 days 5 hours
``````Add submission
`````` Homework 04 --- GAN & VAE
`````` 2021 UC Regents Contact About Privacy Copyright UCLA links | UCLA Registrar MyUCLA Accessibility Couns/PsychSvc (CAPS)