Consider the two class classification task that consists of the following points: Class $C_1: [-1, -1], [-1, 1], [1, -1]$ Class $C_2: [1,1]$ The decision boundary between the two classes $C_1$ and $C_2$ using single perception is given by: $x_1-x_2-0.5=0$ $-x_1-x_2-0.5=0$ $0.5(x_1+x_2)-1.5=0$ $x_1+x_2-0.5=0$

Forward chaining systems are ____ where as backward chaining systems are ____ Data driven, Data driven Goal driven, Data driven Data driven, Goal driven Goal driven, Goal driven

Reasoning strategies used in expert systems include Forward chaining, backward chaining and problem reduction Forward chaining, backward chaining and boundary mutation Forward chaining, backward chaining and back propagation Forward chaining, problem reduction and boundary mutation

A neuron with $3$ inputs has the weight vector $\begin{bmatrix} 0.2 & -0.1 & 0.1 \end{bmatrix}^{T}$ and a bias $\theta =0.$ If the input vector is $X=\begin{bmatrix} 0.2 & 0.4 & 0.2 \end{bmatrix}^{T}$ then the total input to the neuron is: $0.20$ $1.0$ $0.02$ $-1.0$