Data science and big data analysis

Home Blog Data science and big data analysis

Data science and big data analysis

1. What are the two major challenges in the problem of text analysis?
2. What is a reverse index?
3. Why is the corpus metrics dynamic. Provide an example and a scenario that explains the dynamism of the corpus metrics.
4. How does tf idf enhance the relevance of a search result?
5. List and discuss a few methods that are deployed in text analysis to reduce the dimensions.

Add comment

Data Science and Big Data Analysis

Help me study for my Engineering class. I’m stuck and don’t understand.

Guidelines

  • Share screen shot on your response
  • Share the code and the plots
  • Put your name and id number
  • Clear mark question number
  • Upload Word document
  • Insert Cover page Questions Attempted

Week 08 HW

Attached Files:

HW08 Clustering Methods

Q1 Textbook Exercises – Chapter 10 – Unsupervised Learning

Q2 Text Exercises – Applied

8. In Section 10.2.3, a formula for calculating PVE was given in Equation 10.8

On the USArrests data, calculate PVE in two ways:

(a) redo as was done in Section 10.2.3.

(b) By applying Equation 10.8 directly. Then, use those loadings in Equation 10.8 to obtain the PVE. These two approaches should give the same results.

https://botlnec.github.io/islp/sols/chapter10/exercise8/

Q3 Applied K-Means Clustering to the IRIS Dataset

https://www.kaggle.com/tonzowonzo/simple-k-means-clustering-on-the-iris-dataset

Q4 Apply K-Means Clustering to the World Happiness Report 2017

https://www.kaggle.com/unsdsn/world-happiness#2017.csv

Attached data sets and HW08 Template

Add comment

Academic Research Pro