NumPy代写
NumPy代写 C. Nowincrease m, n, p each by a factor of How long do you expect it would take to multiply X and Y using your custom code?
C. Nowincrease m, n, p each by a factor of
- How long do you expect it would take to multiply X and Y using your custom code? How long does it actually take?
- How long do you expect it would take to multiply X and Y using built-in NumPy methods? How long does it actually take?
D. Increasem, n, p each by a factor of l0 again, and repeat the above but using NumPy’s built-in methods How long does it take to multiply X and Y ? Did it increase by the same factor as it did before when all the dimensions were increased by a factor of l0? Why or why not? NumPy代写
E. Generatea n × p matrix and a n-vector y.
- Setn = 5000,p = 200. How long does it take to regress y on X?
- Setn = 50000,p = 200. How long do you expect the same regression would take? How long does it actually take?
- Setn = 5000,p = 2000. How long do you expect the same regression would take? How long does it actually take?
3 Breast *ancer Data NumPy代写
Use the breast cancer data from zklearn to perform the following exercises.
A. Loadthe breast cancer data with the load_breazt_cancer method from the module zklearn.datazetz.
B. Standardizeeach feature in the data
C. PerformPCA on the standardized How many principle components must we keep to explain 90% of the total variance? How much variance is explained if we keep 2?
D. Perform k-means with k =2 on the full set of features, and on the first 2 principle components Compare how well the clusters found by k-means in each of these cases compare to the true targets of the data set.
4 Olivetti Faces NumPy代写
Use the Olivetti faces data set available through zklearn to do the following.
A. Fetchand load the data with the fetch_olivetti_facez method from the module zklearn.datazetz.
B. Demeaneach face in the data set (no need to divide by standard deviation as every dimension is a number between a fixed range representing a pixel).
C. Computeand display the first 9
D. Inclass we showed that any given face in the data set can be represented as a linear combination of the For any face in the data set, show how it progresses as we combine 1, 51, 101,. .. eigenfaces, until the full image is recovered.
更多代写：代写程序 雅思代考 R studio代写 算法代考 Algorithm代做 R代码代写
