# Create a wordlist file using CRUNCH tool - Which category of machine learning algorithm will you choose for this problem

Home, - Demonstrate the use of CRUNCH tool

Question: Demonstrate the using of CRUNCH tool to create a wordlist file to generate a minimum and maximum word length (1-8) based on combination of your MIT ID and two unique special characters. Store the result in file ‘wordlist.txt'. List any two example generated passwords. Demonstrate the use of Hydra Tool to attack an FTP Server ftp://192.168.26.37 with the username "admin". For the password use the wordlist file ‘wordlist.txt' generated using the Crunch Utility in the previous step

Cd/data/crunch
./crunch 1 8 admin -o wordlist.txt

Hydra tool command

Question:
Consider the following Play Dataset, Table 1 (adapted from: Quinlan, "Induction of Decision Trees", Machine Learning, 1986). The dataset shows the data collected over the course of 14 days; the features/attributes are the Outlook, Temperature, Humidity, Wind and the outcome variable is whether Golf was played on the day. Your job is to build a predictive model which takes in the above 4 parameters and predicts whether golf will be played on any given day. Answer the following questions based on the dataset provided

A) Based on the given data, which category of machine learning algorithm will you choose for this problem (Supervised, Unsupervised or Reinforced)? Justify your answer

Based on the provided data, this problem can be solved by using supervised type of the algorithm of machine learning. This is because, the data of this problem is labelled properly. There are values of the records under each label. Day label provides the information of the day. The information of the outlook label is provided by the outlook label. In this all he labels provide the specific information therefore, supervised ML algo, will be best for this case.

B) Given the following information gain for the different attributes: Information Gain for Wind= 0.048 Information Gain for Humidity= 0.151 Information Gain for Temperature= 0.029 Information Gain for Outlook= 0.246 Which attribute should be chosen as the root node?

AS per the given information, the root node is outlook as the information gain value for the outlook attribute is 0.246 which is highest among all other attributes.

C) Suppose we are in the middle of inducing the decision tree. The current state of the decision tree is given below: What will be output on the leaf labelled A?