Hello,
I'm trying to preform PCA analysis for a set of values that I get from the attached excel.
I need to preform the analysis on all 40 variables.
clc
clear all
close all
x=readtable('PCA table.xlsx');
x=table2array(x);
mapcaplot(x)
When I try to use mapcaplot I get the following error:
Index in position 2 exceeds array bounds (must not exceed 1).
Error in mapcaplot>localUpdateBrushPlots (line 201)
ydata = data(:,INDEX_DIM2);
Error in mapcaplot>localInit (line 178)
localUpdateBrushPlots(fig);
Error in mapcaplot (line 65)
localInit(fig,varargin{:});
Error in Untitled (line 7)
mapcaplot(x)
I would appreciate some help. I've never tried to do PCA before and I'm not sure what exactly the function needs as input.
Thank you,
Ruth

1 件のコメント

Star Strider
Star Strider 2021 年 9 月 9 日
If you use the rmmissing funciton on ‘x’, only two rows of valid data remain.

サインインしてコメントする。

 採用された回答

Adam Danz
Adam Danz 2021 年 9 月 9 日

0 投票

See the documentation.
The data input should be a numeric array or a DataMatrix object. Yours is a table.
Also see table2array.

5 件のコメント

Ruth Pikovsky
Ruth Pikovsky 2021 年 9 月 9 日
Hi, thanks for the answer. I did use table2array in my code.
Adam Danz
Adam Danz 2021 年 9 月 9 日
編集済み: Adam Danz 2021 年 9 月 9 日
Sorry, I missed that. The renaming of x threw me off.
The NaN values in your data are the problem (as Star Strider indicated). mapcaplot calls pca() which removes observations with NaN values which results in losing entire rows of data that contain one or more NaN values.
I recommend cleaning up your data, specifically, filling the missing values, if possible.
Ruth Pikovsky
Ruth Pikovsky 2021 年 9 月 9 日
Thank you, the function works now. I'll try to figure out if I can replace the missing NaN values with zeroes.
Adam Danz
Adam Danz 2021 年 9 月 9 日
That will likely affect the pca results, though. Try interpolation if that makes sense for the data.
Ruth Pikovsky
Ruth Pikovsky 2021 年 9 月 10 日
Yeah that's also a good idea. Thank you.

サインインしてコメントする。

その他の回答 (0 件)

カテゴリ

ヘルプ センター および File ExchangeDimensionality Reduction and Feature Extraction についてさらに検索

製品

リリース

R2020a

タグ

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by