1. Smallest Set Covering Intervals
Given a series of integer intervals, determine the size of the smallest set that contains at least one integer within each interval. For example, given the intervals starting at first[i] = [0, 1, 2] and ending at last[i] = [2, 3, 3], the smallest set that contains at least one integer from each interval is {1, 2, 3}. Complete the function 'interval' which has the following parameters: int first[n] (each element represents the start of interval[i]), int last[n] (each element represents the end of interval[i]). The function should return the size of the smallest interval possible. Constraints: 1 <= n <= 10^5, 0 < first[i] < last[i] < 10^5.
2. Sequential String
Given a special string 's' of length 'n' consisting of characters 0-9 only, and an array 'arr' of 'm' strings also consisting of characters 0-9, calculate the minimum number of characters needed from 's' to construct a permutation of each of the strings in 'arr'. Return an array of integers where the ith element denotes the minimum length of a substring that contains a permutation of the string in 'arr'. If a string cannot be constructed, return -1 at that index.
3. House Price Prediction
The task involves data processing and applying regression for house price prediction. The details of the regression requirements are not specified.
4. Submit Predictions on Test Dataset
Submit the predictions on the test dataset using your optimized model. For each record in the test set (test.csv), you must predict whether a customer will cancel his booking or not. You should submit a CSV file with a header row and one row per test entry. The file (submissions.csv) should have exactly 2 columns: id and is_canceled.
5. Build a Classification Model
Build a classification model to determine whether a customer will cancel a booking. Please explain the findings effectively to technical and non-technical audiences using comments and visualizations, if appropriate. Additionally, build an optimized model that effectively solves the business problem. The model's performance will be evaluated on the basis of accuracy. Read the test.csv file and prepare features for testing. Describe the most important features of the model to management and visualize the top 10 features and their feature importance.