Answered: Conisder the following single layer… | bartleby

Related questions

Question

Solve Correctly

Conisder the following single layer trained neural network.
Y=f(Σ,w,X, +t> 0)
where f(2)=
1
0
1
1
Input
nodes
[C, ifz is true
C otherwise
Assigne class labels to the following test data set:
X₁ X2 X3 Y
0
0 0
0
1
1
0
0
1
1
1
0
1
1
1
0
0
X₁
X₂-
X3-
--
Black box
--
W₁=0.2
W₂=0.2
Output
node
EI Y
W₁=-0.5 t=0.2

Expert Solution

Step by step

Solved in 4 steps with 19 images

SEE SOLUTION Check out a sample Q&A here

Blurred answer

Similar questions

What happens if the least remainders algorithm is applied to a pair of consecutive Fibonacci numbers?
def solve_n_queens(n): def is_safe(board, row, col): # Verificar la columna for i in range(row): if board[i][col] == 1: return False # Verificar la diagonal izquierda i, j = row, col while i >= 0 and j >= 0: if board[i][j] == 1: return False i -= 1 j -= 1 # Verificar la diagonal derecha i, j = row, col while i >= 0 and j < n: if board[i][j] == 1: return False i -= 1 j += 1 return True def solve(board, row): if row >= n: solution = [] for r in board: solution.append("".join(['R' if x == 1 else '.' for x in r])) solutions.append(solution) return for col in range(n): if is_safe(board, row, col): board[row][col] = 1 solve(board, row + 1)…
Can you post the code to solve these?
def solve_n_queens(n): def is_safe(board, row, col): # Verificar la columna for i in range(row): if board[i][col] == 1: return False # Verificar la diagonal izquierda i, j = row, col while i >= 0 and j >= 0: if board[i][j] == 1: return False i -= 1 j -= 1 # Verificar la diagonal derecha i, j = row, col while i >= 0 and j < n: if board[i][j] == 1: return False i -= 1 j += 1 return True def solve(board, row): if row >= n: solution = [] for r in board: solution.append("".join(['Q' if x == 1 else '.' for x in r])) solutions.append(solution) return for col in range(n): if is_safe(board, row, col): board[row][col] = 1 solve(board, row + 1)…