Related Questions

What is the term for the process of reducing the dimensionality of data while preserving as much of the variance as possible?
In Data Science, what is the term for the process of reducing the dimensionality of a dataset while preserving information?
In data modeling, what is the term for the process of reducing the dimensionality of data while preserving its important features?
Which of the following statements are true?
Statement I Big data refers to no precise quantity, but generally refers to data in the range of Petabytes and Exabyte, i.e. billions to trillions of records, all from various sources. Big data is generated much faster. than traditional data in much larger quantities.
Statement II Big data interests industries because they are able to learn more patterns and curious variances than smaller data sets, with the capability to provide valuable insights into consumer behaviour, weather systems, financial market activity, or other phenomena.
Statement III Various departments and product lines use various applications within most organisations and store data in separate datasets. These separate databases may contain similar data, but data from one data base to another is not always consistent. This is called data silo.
What is the term for the process of reducing the dimensionality of data while retaining its most important features?
In data science, what is the term for the process of converting text data into numerical form while preserving semantic meaning?
In data science, what is the term for the process of reducing the volume of data while retaining meaningful information?
An electric motor drives a machine through a speed reducing gear of ratio 9:1. The motor armature, with its shaft and gear wheel, has moment of inertia 0.6 kg-m2. The rotating part of the driven machine has moment of inertia 45 kg-m2. The driven machine has resisting torque of 100 N-m and the efficiency of reduction gear is 95%. Find the power which the motor must develop to drive the machine at a uniform speed of 160 r.p.m.
Which one of the following is true with regard to a CPU having a single interrupt request line and single interrupt grant line? i) Neither vectored nor multiple interrupting devices is possible. ii) Vectored interrupts is not possible but multiple interrupting devices is possible. iii) Vectored interrupts is possible and multiple interrupting devices is not possible. iv) Both vectored and multiple interrupting devices are possible.
In R, which package is commonly used for dimensionality reduction and feature extraction in machine learning?