Try to implement stop words removal in your feature engineering code. Specifically, load the file stopwords. txt, remove the words in the file from your dictionary, and use features constructed from the new dictionary to train your model and make predictions. Compare your result in the testing data on Pegasos algorithm using T=25 and L=0.01 when you remove the words in stopwords. txt from your dictionary. Hint: Instead of replacing the feature matrix with zero columns on stop words, you can modify the bag_of_words function to prevent adding stopwords to the dictionary Accuracy on the test set using the original dictionary: 0.8020 Accuracy on the test set using the dictionary with stop words removed:

In which phase does software coding and testing happen in the spiral model? the spiral model does not have a separate testing phase. both, software coding and testing occurs during the phase.

Acloud service provider uses the internet to deliver a computing environment for developing, running, and managing software applications. which cloud service model does the provider offer? a. iaas b. caas c. maas d. paas e. saas

Given a link with a maximum transmission rate of 32.8 mbps. only two computers, x and y, wish to transmit starting at time t = 0 seconds. computer x sends filex (4 mib) and computer y sends filey (244 kib), both starting at time t = 0. statistical multiplexing is used, with details as follows packet payload size = 1000 bytes packet header size = 24 bytes (overhead) ignore processing and queueing delays assume partial packets (packets consisting of less than 1000 bytes of data) are padded so that they are the same size as full packets. assume continuous alternating-packet transmission. computer x gets the transmission medium first. at what time (t = ? ) would filey finish transmitting? give answer in milliseconds, without units, and round to one decimal places (e.g. for an answer of 0.013777 seconds you would enter "13.8" without the quotes)