Move furtively

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Last seen on: –Daily Celebrity Crossword – 5/13/19 Movie Monday
Eugene Sheffer – King Feature Syndicate Crossword – Mar 27 2019 Crossword – Feb 26 2019 Crossword – Nov 25 2018
NY Times Crossword 6 Jul 2018, Friday
-Eugene Sheffer – King Feature Syndicate Crossword – May 24 2018

Random information on the term “CREEP”:

President of the United States

First term

Second term


The presidency of Richard Nixon began on January 20, 1969, when he was inaugurated, and ended on August 9, 1974, when he resigned in the face of almost certain impeachment and removal from office, the first U.S. president ever to do so. He was succeeded by Vice President Gerald Ford, who had become vice president nine months earlier, following Spiro Agnew’s resignation from office. A Republican, Nixon took office after the 1968 presidential election, in which he defeated Hubert Humphrey, the then–incumbent Vice President. Four years later, in 1972, Nixon won reelection in a landslide victory over George McGovern.

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Nixon, the 37th United States president, succeeded Lyndon B. Johnson, who had launched the Great Society, a set of domestic programs financed and run by the federal government. In contrast, Nixon advocated a “New Federalism” domestic program model, one in which certain powers would devolve back to the states. The creation of the EPA, passage of the Endangered Species Act, and the integration of Southern public schools happened during his presidency, as did the end of military draft and the Apollo program, which successfully landed Americans on the Moon.

CREEP on Wikipedia

Random information on the term “SLINK”:

In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known. An example would be assigning a given email into “spam” or “non-spam” classes or assigning a diagnosis to a given patient as described by observed characteristics of the patient (gender, blood pressure, presence or absence of certain symptoms, etc.). Classification is an example of pattern recognition.

In the terminology of machine learning, classification is considered an instance of supervised learning, i.e. learning where a training set of correctly identified observations is available. The corresponding unsupervised procedure is known as clustering, and involves grouping data into categories based on some measure of inherent similarity or distance.

Often, the individual observations are analyzed into a set of quantifiable properties, known variously as explanatory variables or features. These properties may variously be categorical (e.g. “A”, “B”, “AB” or “O”, for blood type), ordinal (e.g. “large”, “medium” or “small”), integer-valued (e.g. the number of occurrences of a particular word in an email) or real-valued (e.g. a measurement of blood pressure). Other classifiers work by comparing observations to previous observations by means of a similarity or distance function.

SLINK on Wikipedia