Write a method that takes in an array of point2d objects, and then analyzes the dataset to find points that are close together. be sure to review the point2d api. in your method, if the distance between any pair of points is less than 10, display the distance and the (x, y)s of each point. for example, "the distance between (3,5) and (8,9) is 6.40312." the complete api for the point2d adt may be viewed at ~pf/sedgewick-wayne/algs4/documenta tion/point2d. html (links to an external site.)links to an external site.. try to write your program directly from the api - do not review the adt's source code.

Your task this week is to write a very simple spam classifier in python. it will classify messages as either spam (unwanted) or ham (wanted). the program will have a set of spam_words, words that are known to appear in spam messages. that set is included in the template file spam.pypreview the document. you will also define a spam threshold which reflects the allowed percentage of spam words in the message. you'll compute a 'spam indicator', which is the ratio of spam words to the total number of unique words in the message. if the spam indicator exceeds the spam threshold, the message is classified as spam. otherwise it is classified as ham. we'll assume that the spam threshold is a constant and has a value of 0.10. your program will prompt the user for a message and then will print the corresponding spam indicator with two decimal digits and the corresponding classification (spam or ham). the program will be case insensitive. the spam words are detected whether they are in lower case or upper case or mixed case. each word, spam or not, is counted once (even if it appears multiple times in the message.) the program will remove punctuation from the message before identifying the words and computing the spam indicator. for example '! ' must be identified as the spam word 'now'.

What result from the passage of this amendment

Wich technology can a website use to allow you to listen to a concert live over the internet?