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Recent questions tagged goclasses-da-course

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Go Classes | DA Course | Machine Learning
Recall that the output of a perceptron is 0 or 1 . For each of the two following data sets, select the perceptron network with the fewest nodes that will separate the cla...
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Go Classes | DA Course | Machine Learning
Consider the unit shown on Figure 1. Suppose that the weights corresponding to the three inputs have the following values:$w_1= 2$$w_2 = - 4$$w_3= 1$and the activation of...
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Go Classes | DA Course | Machine Learning
Suppose that we are performing a prediction task using artificial neurons. Which of the following statements about artificial neurons is TRUE?Linear regression uses the i...
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Go Classes | DA Course | Machine Learning
Can a neural network be used to model the following machine learning algorithms?Linear regressionLogistic regressionK-nearest neighbour 123None
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Go Classes | DA Course | Machine Learning
What is the output(round to 2 decimal points) of the network for $x_1 =1,x_2 = 1$? Assume sigmoid is being at $a1, a2$ and at $y$ no activation function is used. 
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Go Classes | DA Course | Machine Learning
What is the output of the network for $x_1 = 1,x_2 = 2 $. Assume at every level identity function is used.
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Go Classes | DA Course | Machine Learning
Using this dendrogram to create 3 clusters, what would the clusters be?{BA, NA}, {RM, FI}, {MI, TO}{NA, RM}, (BA, FI}, (MI, TO}{BA, NA, RM, FI}, {MI}, {TO}{BA, NA, RM}, {...
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Go Classes | DA Course | Machine Learning
Perform agglomerative Hierarchical Clustering using single linkage as the cluster distance measure . Draw the associated tree. 
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Go Classes | DA Course | Machine Learning
Perform both Single Linkage and Complete Linkage clustering on the given 2D points.Use the visible distances as reference. 
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Go Classes | DA Course | Machine Learning
There are five points in one-dimensional space: $a = 0,6 = 1, c = 3, d = 7, e = 9$. Perform Hierarchical Agglomerative Clustering with complete linkage. Complete the resu...
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Go Classes | DA Course | Machine Learning
Perform hierarchical clustering with single linkage in one-dimensional space on the following points: $-5, -1, 0, 3, 9, 11$. Draw the clustering tree.
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Go Classes | DA Course | Machine Learning
There are five points in one-dimensional space: $a=1.5, b=2, c=6, d=7, e=9.$ Perform Hierarchical Agglomerative Clustering with Single Linkage, with the following extra c...
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Go Classes | DA Course | Machine Learning
Perform the K-Medoid algorithm for $\mathrm{K}=2$ on the given dataset, assuming that points D and E are chosen as the initial medoid centers.
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Go Classes | DA Course | Machine Learning
A good way to pick the number of clusters, $k$, used for $k$-Means clustering is to try multiple values of $k$ and choose the value that minimizes the distortion measure....
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Go Classes | DA Course | Machine Learning
$\text { In which of the following plots are the points clustered by } k \text {-means clustering ? }$abboth a and bNeither a nor b
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Go Classes | DA Course | Machine Learning
Euclidean distance based $k$-means clustering algorithm was run on a dataset of 100 points with $k=3$. If the points $\left[\begin{array}{l}1 \\ 1\end{array}\right]$ and ...
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Go Classes | DA Course | Machine Learning
Given the dataset: $(1,1),(3,3),(4,4),(5,5),(6,6),(9,9),(0,3),(3,0)$ and assuming the initial centroids for ( $K=3$ - means clustering) to be $C_1=$ $(3,3), C_2=(5,5)$ an...
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Go Classes | DA Course | Machine Learning
$K$-means algorithm always finds the clustering $\left(C_1, \ldots, C_K\right)$ that minimizes the objective:Minimize $\sum_{k=1}^K \sum_{t \in C_j}\left\|x_t-r_j\right\|...
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Go Classes | DA Course | Machine Learning
Recall the loss function for $k$-means clustering with $k$ clusters, sample points $x_1, \ldots, x_n$, and centers $\mu_1, \ldots, \mu_k$ :$$L=\sum_{j=1}^k \sum_{x_i \in ...
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Go Classes | DA Course | Machine Learning
Recall the $k$-means objective function is$$L\left(z_{1: n}, \mu_{1: k}\right)=\sum_{i=1}^n\left\|x^{(i)}-\mu_{z_i}\right\|^2$$where $z_{1: n}$ are the cluster assignment...
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Go Classes | DA Course | Machine Learning
Recall the $k$-means objective function is$$L\left(z_{1: n}, \mu_{1: k}\right)=\sum_{i=1}^n\left\|x^{(i)}-\mu_{z_i}\right\|^2$$where $z_{1: n}$ are the cluster assignment...
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Go Classes | DA Course | Machine Learning
Amazing, Inc. plans to open $k=2$ stores in Megacity and has $n=4$ customers located at positions $x^{(i)}$ as shown by circles in the plot below. The initial guesses for...
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Go Classes | DA Course | Machine Learning
You want to cluster 7 points into 3 clusters using the $\boldsymbol{k}$-Means Clustering algorithm. Suppose after the first iteration, clusters $\mathrm{C}_1, \mathrm{C}_...
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Go Classes | DA Course | Machine Learning
Calculate the misclassification error rate of a decision tree node containing the following dataset: \begin{array}{c|c}\text { Class } & \text { Count } \\\hline \text { ...
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Go Classes | DA Course | Machine Learning
Calculate the misclassification error rate of a decision tree node containing the following dataset:\begin{array}{c|c}\text { Class } & \text { Count } \\\hline \text { C...
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Go Classes | DA Course | Machine Learning
Consider the following dataset with input $x \in \mathbb{R}^3$ and $y \in\{0,1\}$. Both $x_i$ and $y$ are binary random variables.\begin{array}{cccc}x_1 & x_2 & x_3 & \ma...
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Go Classes | DA Course | Machine Learning
What is the conditional entropy, $H(C \mid A)$, for the following set of 8 training examples.Use $\log 0.1=-3.3, \log 0.2=-2.3, \log 0.25=-2.0, \log 0.3=-1.74, \log 0.33=...
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Go Classes | DA Course | Machine Learning
$\text { Consider the following set of training examples: }$\begin{array}{|l|c|c|c|}\hline \text { Instance } & \text { Classification } & \mathbf{X}_{\mathbf{1}} & \math...
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Go Classes | DA Course | Machine Learning
$\text { What is the entropy of } Y \text {, i.e., } H(Y) \text { ? }$\begin{array}{|c|c|c|c|c|}\hline X_1 & 0 & 0 & 1 & 1 \\\hline X_2 & 0 & 1 & 0 & 1 \\\hline Y & 1 & 1...
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Go Classes | DA Course | Machine Learning
Which attribute (Age, Salary, Marital Status) should be placed at the top of the decision tree? Justify your choice using entropy.Car Type is the target attribute\begin{a...
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