Question
Which technique is used to reduce dimensionality while
preserving variance?Solution
Principal Component Analysis reduces dimensionality by transforming the data into components that retain the most variance.
306, 272, 240, ?, 182, 156
22, 37, 63, 98, 148, ?
What will come in place of the question mark (?) in the following series?
4000, ?, 320, 192, 153.6, 153.6
58, 63, 78, ?, 138, 183
10, ?, 50, 100, 250, 500
96 89 ? 90 94 91
...What will come in place of the question mark (?) in the following series?
34, 61, 7, ?, -20, 115
The question below is based on the given series I. The series I satisfy a certain pattern, follow the same pattern in series II and answer the questions...
321, 240, ?, 105, 51, 6
15   8   9   15   32    ?    250.5