lab 5 assignment - naveenanallamotu/Big-Data-Analytics-Lab-Assignments GitHub Wiki

1)Image classification with Machine learning: I used NavieBayesModel as the classification model and for clustering, it k-Means Input: image data set Description of dataset: Trained data I have given the images of different breeds of dogs like the bulldog, labrador, Yorkshire, german Sheperd as my trained data.

Test data In the test data, I have given the images of dogs with human beings.

Purpose In here we try to the Identify the same breed dog (even it is different) from another set of images we given in the test data which is having dogs with human beings

Confusion matrix: A confusion matrix is a table that is often used to describe the performance of the classification model on the set of test data for which the true values are known Predicting test

Output:

Predicting test image : yorkshire as bulldog (0.0,3) (0.0,3) (0.0,3) (0.0,3) (0.0,3) (0.0,2) (0.0,2) (0.0,2) (0.0,2) (3.0,1) (0.0,1) (0.0,1) (0.0,1) (0.0,0) (0.0,0) (0.0,0) (0.0,0) (0.0,0) 0.2777777777777778 |=================== Confusion matrix ========================== 5.0 0.0 0.0 0.0
3.0 0.0 0.0 1.0
4.0 0.0 0.0 0.0
5.0 0.0 0.0 0.0
0.2777777777777778

2)Client-server communication: First, we need to open a port for 8081 for npm web client and need to run the program in IntelliJ(server) and image classification model we used in the program is random forest model. The images in client need to be predicted Input: Breeds of dogs. Output: prediction of breed of given dog(Screenshot will be given in the documentation folder)

  1. Google conversation with API.AI: api.ai is used for creation and integration sophisticated conversational interfaces as simple as possible. The following are the essential things while building our own Conversational one. Agent: Agents can be described as NLU (Natural Language Understanding) modules for applications Intent: An intent represents a mapping between what a user says and what action should be taken by your software Entity: Entities represent concepts and serve as a powerful tool for extracting parameter values from natural language inputs Integration: We use Google Web simulator to preview our code and the invocation Id I have Given to it is Hi,navi Screenshots for this is provided in the documentation folder Fulfillments: we added to app webhook. output Screenshots is kept in the documentation folder.