2048: Curve-Fitting - Revision history

TheusafBOT: Reverted edit 391316 by 122.171.23.189 to 391315

2025-11-20T10:11:36Z

Reverted edit 391316 by 122.171.23.189 to 391315

122.171.23.189 at 10:11, 20 November 2025

2025-11-20T10:11:02Z

TheusafBOT: Reverted edit 391314 by 122.171.23.189 to 384718

2025-11-20T10:08:36Z

Reverted edit 391314 by 122.171.23.189 to 384718

122.171.23.189 at 10:08, 20 November 2025

2025-11-20T10:08:06Z

CalibansCreations: /* LOESS */

2025-08-21T15:52:59Z

‎LOESS

172.71.242.168: Undo revision 344546 by 162.158.114.103 (talk) Introduced a mathml error... (Does nobody ever Preview such things?)

2024-06-18T20:09:18Z

Undo revision 344546 by 162.158.114.103 (talk) Introduced a mathml error... (Does nobody ever Preview such things?)

162.158.114.103: redundancy

2024-06-18T14:49:50Z

redundancy

172.70.100.140: /* House of Cards */

2024-02-16T19:03:28Z

‎House of Cards

172.70.86.18: /* Connecting lines */

2023-12-20T00:58:55Z

‎Connecting lines

172.70.86.67: Undo revision 331169 by 172.70.207.105 (talk) Logarithmic doesn't settle to asymptote, so these data (hypothetically) doing so is not fit by that.

2023-12-20T00:49:37Z

Undo revision 331169 by 172.70.207.105 (talk) Logarithmic doesn't settle to asymptote, so these data (hypothetically) doing so is not fit by that.

@@ Line 1: / Line 1: @@
 {{comic
 | number    = 2048
-| date      = Wiki-dstyle.png
+| date      = September 19, 2018
-| title     = Wiki-dstyle.png
+| title     = Curve-Fitting
 | image     = curve_fitting.png
 | titletext = Cauchy-Lorentz: "Something alarmingly mathematical is happening, and you should probably pause to Google my name and check what field I originally worked in."

@@ Line 1: / Line 1: @@
 {{comic
 | number    = 2048
-| date      = September 19, 2018
+| date      = Wiki-dstyle.png
-| title     = Curve-Fitting
+| title     = Wiki-dstyle.png
 | image     = curve_fitting.png
 | titletext = Cauchy-Lorentz: "Something alarmingly mathematical is happening, and you should probably pause to Google my name and check what field I originally worked in."

@@ Line 3: / Line 3: @@
 | date      = September 19, 2018
 | title     = Curve-Fitting
-| image     = Wiki-dstyle.png
+| image     = curve_fitting.png
 | titletext = Cauchy-Lorentz: "Something alarmingly mathematical is happening, and you should probably pause to Google my name and check what field I originally worked in."
 }}

@@ Line 3: / Line 3: @@
 | date      = September 19, 2018
 | title     = Curve-Fitting
-| image     = curve_fitting.png
+| image     = Wiki-dstyle.png
 | titletext = Cauchy-Lorentz: "Something alarmingly mathematical is happening, and you should probably pause to Google my name and check what field I originally worked in."
 }}

@@ Line 53: / Line 53: @@
 ===LOESS===
-A {{w|Local regression|LOESS fit}} doesn't use a single formula to fit all the data, but approximates data points locally using different polynomials for each "zone" (weighting data points differently as they get further from it) and patching them together. As it has many more degrees of freedom compared to a single polynomial, it generally "fits better" to any data set, although it is generally impossible to derive any strong, "clean" mathematical correlation from it - it is just a nice smooth line that approximates the data points well, with a good degree of rejection from outliers.
+A {{w|Local regression|LOESS fit}} (locally estimated scatterplot smoothing) doesn't use a single formula to fit all the data, but approximates data points locally using different polynomials for each "zone" (weighting data points differently as they get further from it) and patching them together. As it has many more degrees of freedom compared to a single polynomial, it generally "fits better" to any data set, although it is generally impossible to derive any strong, "clean" mathematical correlation from it - it is just a nice smooth line that approximates the data points well, with a good degree of rejection from outliers.
 The comment below the graph ''"I'm sophisticated, not like those bumbling polynomial people."'' emphasises this more complicated interpretation, but without a simple mathematical description it's not very helpful to find informative interpretations of the underlying data.

@@ Line 36: / Line 36: @@
 ===Logarithmic===
 [[File:Logarithm_plots.png|thumb|200px|Common logarithm functions.]]
-<math>f(x) = a\ln(x)</math>
+<math>f(x) = a\log_b(x)</math>
 A {{w|Logarithm|logarithmic}} curve grows slower on higher values, but still grows without bound to infinity rather than approaching a horizontal {{w|asymptote}}. The small ''b'' in the formula represents the base which is in most cases ''{{w|e (mathematical constant)|e}}'', 10, or 2. If the data presumably does approach a horizontal asymptote then this fit isn't an effective method to explain the nature of the data.

← Older revision		Revision as of 19:03, 16 February 2024
Line 110:		Line 110:

	The comment below the graph ''"As you can see, this model smoothly fits the- wait no no don't extend it AAAAAA!!"'' refers to a curve which fits the data points relatively well within the graph's boundaries, but beyond those bounds fails to match at all.		The comment below the graph ''"As you can see, this model smoothly fits the- wait no no don't extend it AAAAAA!!"'' refers to a curve which fits the data points relatively well within the graph's boundaries, but beyond those bounds fails to match at all.
−
−	The name is also a potential reference to the TV show ''{{w\|House of Cards (U.S. TV series)\|House of Cards}}''. The plot in House of Cards began with a premise of a rise to power in the United States government, but as it continued into more seasons the premise was taken to an extreme, introducing more and more ridiculous plot points ("WAIT NO, NO, DON'T EXTEND IT!").

	===Cauchy-Lorentz (title text)===		===Cauchy-Lorentz (title text)===

@@ Line 97: / Line 97: @@
 This is often used to smooth gaps in measurements. A simple example is the weather temperature which is often measured in distinct intervals. When the intervals are high enough it's safe to assume that the  temperature didn't change that much between them and connecting the data points by lines doesn't distort the real situation in many cases.
-The comment below the graph ''"I clicked 'Smooth Lines' in {{w|Microsoft Excel|Excel}}."'' refers to the well known spreadsheet application from {{w|Microsoft Office}}. Like other spreadsheet applications it has the feature to visualize data from a table into a graph by many ways. "Smooth Lines" is a setting meant for use on a {{w|line graph}}, a graph in which one axis represents time; as it simply joins up every point rather than finding a sensible line, it is not suitable for regression.
+The comment below the graph ''"I clicked 'Smooth Lines' in {{w|Microsoft Excel|Excel}}."'' refers to the well known spreadsheet application from {{w|Microsoft Office}}. Like other spreadsheet applications it has the feature to visualize data from a table into a graph by many ways. "Smooth Lines" is a setting meant for use on a {{w|line graph}}, a graph in which one axis represents time; as it simply joins up every point using bezier (or similar) curves as necessary to pass through every point (rather than finding a more sensible line that accepts some minimal but non-zero acceptible level of error in the datapoints), it is not suitable for regression.
 ===Ad-Hoc Filter===

@@ Line 38: / Line 38: @@
 <math>f(x) = a\log_b(x)</math>
-A {{w|Logarithm|logarithmic}} curve grows slower on higher values, but still grows without bound to infinity rather than approaching a horizontal {{w|asymptote}}. The small ''b'' in the formula represents the base which is in most cases ''{{w|e (mathematical constant)|e}}'', 10, or 2. If the data presumably doesn't approach a horizontal asymptote then this fit isn't an effective method to explain the nature of the data.
+A {{w|Logarithm|logarithmic}} curve grows slower on higher values, but still grows without bound to infinity rather than approaching a horizontal {{w|asymptote}}. The small ''b'' in the formula represents the base which is in most cases ''{{w|e (mathematical constant)|e}}'', 10, or 2. If the data presumably does approach a horizontal asymptote then this fit isn't an effective method to explain the nature of the data.
 The comment below the graph ''"Look, it's tapering off!"'' builds up the impression that the data diminishes while under this fit it's still growing to infinity, only much slower than a linear regression does.