is it possible to invent a dataset and a positive value of C in which the dataset is linearly seperable but the linear SVM classi er would never the less misclassify at least one training point?

4.9: population write a program that will predict the size of a population of organisms. the program should ask the user for the starting number of organisms, their average daily population increase (as a percentage, expressed as a fraction in decimal form: for example 0.052 would mean a 5.2% increase each day), and the number of days they will multiply. a loop should display the size of the population for each day. prompts, output labels and messages.the three input data should be prompted for with the following prompts: "enter the starting number organisms: ", "enter the daily increase: ", and "enter the number of days the organisms will multiply: " respectively. after the input has been read in successfully, a table is produced, for example: 2 300.0 4 675.0 under the heading is a line of 29 dashes followed by one line for each day, showing the day number and the population at the beginning of that day. input validation.do not accept a number less than 2 for the starting size of the population. if the user fails to satisfy this print a line with this message "invalid. must be at least 2. re-enter: " and try to read the value. similarly, do not accept a negative number for average daily population increase, using the message "invalid. enter a non-negative number: " and retrying. finally, do not accept a number less than 1 for the number of days they will multiply and use the message "invalid. enter 1 or more: ".