1. Where: N: Number of model states A: Transition probability matrix B: Output probability matrix Pi: Initial state probability matrix T: Training data 2. Your Python code: def BaumWelch(N,A,B,Pi,T) : return [A,B,Pi] # Trained Model 3. Return re-estimated A, B and Pi matrices Notes: Your code must be original work - That is: it must not be a copy of code found online. Submit your python code in a separate file named “viterbi_.py" As Outlook filters out executable files, submit your work in a .zip file A write-up describing the Baum-Welch algorithm and your implementation of it Note: Be sure to list all references Your hand calculations for the first observation vector 1. 2. 3.

1. Where: N: Number of model states A: Transition probability matrix B: Output probability matrix Pi: Initial state probability matrix T: Training data 2. Your Python code: def BaumWelch(N,A,B,Pi,T) : return [A,B,Pi] # Trained Model 3. Return re-estimated A, B and Pi matrices Notes: Your code must be original work - That is: it must not be a copy of code found online. Submit your python code in a separate file named “viterbi_.py" As Outlook filters out executable files, submit your work in a .zip file A write-up describing the Baum-Welch algorithm and your implementation of it Note: Be sure to list all references Your hand calculations for the first observation vector 1. 2. 3.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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1. 2. Your Python code: def Baum Welch(N,A,B,Pi,T) : Where: N: Number of model states A: Transition probability matrix B: Output probability matrix Pi: Initial state probability matrix T: Training data 3. 4. return [A,B,Pi] # Trained Model Return re-estimated A, B and Pi matrices Notes: 1. Your code must be original work - That is: it must not be a copy of code found online. 2. Submit your python code in a separate file named "viterbi_.py" 3. As Outlook filters out executable files, submit your work in a .zip file A write-up describing the Baum-Welch algorithm and your implementation of it Note: Be sure to list all references Your hand calculations for the first observation vector A sample run for each of the three observation vectors
NOTE: WRITE IN C# Write a distributed probability random number generator using one of the probability sampling methods (like rejection sampling). Explain the codes and the sampling implementation in detail. Example: İnputs : (3, 0.4) (5, 0.5) Output: Generated random number is 3, it has %40 probability Generated random number is 5, it has %50 probability NOTE: WRITE IN C# NOTE: MAKE A GENERIC SOLUTION THAT APPLIES FOR ANY GIVEN NUMBER AND PROBABILITY. NOT JUST BASED ON THIS EXAMPLE !!!
Loops summary: for vs. while We have now seen that Python has two different loop constructs: the for loop and the while loop. The while loop is more powerful than the for loop, since it can be used in situations where the number of iterations isn't known in advance. For example, the following while loop answers the question: "If a population of bacteria increases in size by 21% every minute, how long does it take for the population size to double?" minutes = 0 population = 1000 growth_rate = 0.21 while population < 2000: population *= (1 + growth_rate) minutes += 1 print (f"{minutes} minutes required.") print (f"Population = {int(population)}") This would not be well suited to a for loop - we are trying to find out how many times the loop will run, and a for loop expects to know how many times it will run before it starts. In contrast, the for loop is a special case of the more general while loop, meaning that any program written with for loops can be rewritten to use while loops.…
1. fInd the average win and lose rate of the crabs game 2. Find the Mean, Median, and mode of how long a player takes until he wins and loses a game.Basically find out how long each game lasts. With mean, median, and mode. This code is for python and its for the craps game. Below is the code I have so far. import randomimport sysimport pandas as pddef roll_dice():die1 = random.randrange(1, 7)die2 = random.randrange(1, 7)return (die1, die2)def display_dice(dice):die1, die2 = diceprint(f'Player rolled {die1} + {die2} = {sum(dice)}')# List that stores number of wins on every rollwinList = []# List that stores number of losses on every rolllossList = []# List that stores label indexes of horizontal bar plotylabel = []# 1# number of games of crapsn = int(input("Enter number of games: "))# Iterating 13 times# Because it is mentioned in the question that plot should have 13# horizontal bars for wins, and 13 horizontal bars for losses.for roll in range(13):ylabel.append('Roll ' + str(roll +…
Exercise 2: In probability theory, one problem that often arises is determining the number of ways in which p objects can be selected from n distinct objects without regard to the order in which they are selected. Such selections are called combinations. The number of combinations of p objects from a set with n objects is C (n, p) and is given by: п! С(п, р) — (п- р)! * p! Write a Python program which will calculate and display on the screen the number of possible combination C based on the values of n and p; where both n and p are positive integers less than 21 and n >p. Implement and use at least the following three functions: fact(.): A function when passed a positive integer value, will calculate and return the factorial of that number. comb(..): A function when passed n and p (n: total number of objects and p: number of objects taken at a time) will calculate and return the total number of possible combinations (using the formula above). It calls function fact.) main(..): reads…
#In the lines below, I wrote a quick program used to simulate a stock price over two years. As an#investor, I want to know what the longest run was of consecutive gains was in the dataset (e.g.#10.2,13,42,89,85 has a run of three where the price rose before a drop.) Print the length of the longest#run and the members of that run.import numpy as npvec = np.random.uniform(80, 120, 720)print(vec)
In Python, Compute the: sum of squares total (SST), sum of squares regression (SSR), sum of squares error(SSE), and the r, R^2 values. You can use the sum() and mean() built-in functions. Here are the x and y values to use. x = [-5,-1,3,7,5,10] y = [-10,-3,5,8,7,10]
Python(multiple linear regression using Ordinary Least Square method) Question: Implement multiple linear regression using Ordinary Least Square method from scratch in Python. ****You are required to at least write your own the fit(), predict(), r2_score() method. Use the following dataset: titanic_train.csv, titanic_test.csv (both can be found online ,files are large so can't attach) Target: Predict whether or not the passenger survived the sinking of the Titanic. Remove unnecessary features if any. Note: do not copy paste any answer available online or in archive I want a personalised answer from an expert do display the output of an running program add comments for better understanding of solution
Exercise 2: In probability theory, one problem that often arises is determining the number of ways in which p objects can be selected from n distinct objects without regard to the order in which they are selected. Such selections are called combinations. The number of combinations ofp objects from a set with n objects is C (n, p) and is given by: n! C(n, p) = (п - р)! * р! Write a Python program which will calculate and display on the screen the number of possible combination C based on the values of n and p; where both n and p are positive integers less than 21 and n> p. Implement and use at least the following three functions: fact(..): A function when passed a positive integer value, will calculate and return the factorial of that number. comb(.): A function when passed n and p (n: total number of objects and p: number of objects taken at a time) will calculate and return the total number of possible combinations (using the formula above). It calls function fact(.) main(..): reads…
Problem Y: Implement the reader writer problem using pthreads and semaphores. You should allow multiple readers to read at the same time and only one single writer to write to the data set. You are required to use the following: 1. A semaphore rw_muter initialized to 1. 2. A semaphore muter initialized to 1. 3. An integer reader_count initialized to 0.
import stdio import sys x = sys.argv [1:] for v in x: stdio.write (v + stdio.writeln () If the program is run as follows: $ python3 mystery.py Fred Carol Bob Alice Dan Eve Grace a. What is the value of the expression len (sys.argv)? A 7 B E 5 8 6
Python Language Q2: Ginormous Campus The campus is pretty big. There are n buildings scattered around it, numbered from 0 to n-1. These buildings are so far away from each other that the only way to get from one to another is to take a campus bus. There are m campus bus routes. The i-th one (0 <= i < m) takes you from building u_i to building v_i (but not the other way around). These buses run very frequently. Professor Zingaro is deciding where to hold his CS lectures. He believes a building x is accessible from a building y if you can get from y to x taking at most two buses. For his students’ convenience, he wants to hold his lectures in the most accessible building. Help him out by telling him how many buildings the most accessible building is accessible from. In addition, list all buildings that are the most accessible. Input The first line of the input contains two space-separated integers n and m, denoting the number of buildings and bus routes, respectively. m lines…