feat: update dependencies

Also fixes the build.

eslint.config.mjs

@@ -0,0 +1,11 @@
+import cheminfo from "eslint-config-cheminfo/base";
+import globals from "globals";
+
+export default [
+  ...cheminfo,
+  {
+    languageOptions: {
+      globals: { ...globals.jest },
+    },
+  },
+];

package.json

@@ -41,24 +41,25 @@
     "testEnvironment": "node"
   },
   "devDependencies": {
-    "@babel/plugin-transform-modules-commonjs": "^7.24.1",
-    "@types/jest": "^29.5.12",
-    "eslint": "^8.57.0",
-    "eslint-config-cheminfo": "^9.2.0",
+    "@babel/plugin-transform-modules-commonjs": "^7.25.7",
+    "@types/jest": "^29.5.13",
+    "eslint": "^9.12.0",
+    "eslint-config-cheminfo": "^12.0.1",
+    "globals": "^15.11.0",
     "jest": "^29.7.0",
-    "prettier": "^3.2.5",
-    "rollup": "^4.17.2"
+    "prettier": "^3.3.3",
+    "rollup": "^4.24.0"
   },
   "dependencies": {
     "ml-kernel": "^3.0.0",
-    "ml-matrix": "^6.11.0",
-    "ml-regression-base": "^3.0.0",
-    "ml-regression-exponential": "^2.1.0",
+    "ml-matrix": "^6.12.0",
+    "ml-regression-base": "^4.0.0",
+    "ml-regression-exponential": "^3.0.1",
     "ml-regression-multivariate-linear": "^2.0.4",
-    "ml-regression-polynomial": "^3.0.0",
-    "ml-regression-power": "^2.0.0",
+    "ml-regression-polynomial": "^3.0.1",
+    "ml-regression-power": "^3.0.0",
     "ml-regression-robust-polynomial": "^3.0.0",
-    "ml-regression-simple-linear": "^3.0.0",
-    "ml-regression-theil-sen": "^2.0.0"
+    "ml-regression-simple-linear": "^3.0.1",
+    "ml-regression-theil-sen": "^3.0.0"
   }
 }

src/index.js

@@ -1,24 +1,24 @@
-import PotentialRegression from "./regression/potential-regression";
+import { PotentialRegression } from "./regression/potential-regression";
 
 export {
   SimpleLinearRegression,
   SimpleLinearRegression as SLR,
 } from "ml-regression-simple-linear";
 export { PolynomialRegression } from "ml-regression-polynomial";
-export { default as ExponentialRegression } from "ml-regression-exponential";
-export { default as PowerRegression } from "ml-regression-power";
+export { ExponentialRegression } from "ml-regression-exponential";
+export { PowerRegression } from "ml-regression-power";
 export { default as MultivariateLinearRegression } from "ml-regression-multivariate-linear";
 const NLR = {
   PotentialRegression,
 };
 export { NLR, NLR as NonLinearRegression };
 
 export {
-  default as KernelRidgeRegression,
-  default as KRR,
+  KernelRidgeRegression,
+  KernelRidgeRegression as KRR,
 } from "./regression/kernel-ridge-regression";
-export { default as PolinomialFitting2D } from "./regression/poly-fit-regression2d";
+export { PolynomialFitRegression2D as PolinomialFitting2D } from "./regression/poly-fit-regression2d";
 
 // robust regressions
-export { default as TheilSenRegression } from "ml-regression-theil-sen";
+export { TheilSenRegression } from "ml-regression-theil-sen";
 export { RobustPolynomialRegression } from "ml-regression-robust-polynomial";

src/regression/kernel-ridge-regression.js

@@ -1,6 +1,6 @@
 import Kernel from "ml-kernel";
 import { Matrix, solve } from "ml-matrix";
-import BaseRegression from "ml-regression-base";
+import { BaseRegression } from "ml-regression-base";
 
 const defaultOptions = {
   lambda: 0.1,
@@ -11,7 +11,7 @@ const defaultOptions = {
 
 // Implements the Kernel ridge regression algorithm.
 // http://www.ics.uci.edu/~welling/classnotes/papers_class/Kernel-Ridge.pdf
-export default class KernelRidgeRegression extends BaseRegression {
+export class KernelRidgeRegression extends BaseRegression {
   constructor(inputs, outputs, options) {
     super();
     if (inputs === true) {

src/regression/poly-fit-regression2d.js

@@ -1,12 +1,12 @@
 import { Matrix, SVD } from "ml-matrix";
-import BaseRegression from "ml-regression-base";
+import { BaseRegression } from "ml-regression-base";
 
 const defaultOptions = {
   order: 2,
 };
 // Implements the Kernel ridge regression algorithm.
 // http://www.ics.uci.edu/~welling/classnotes/papers_class/Kernel-Ridge.pdf
-export default class PolynomialFitRegression2D extends BaseRegression {
+export class PolynomialFitRegression2D extends BaseRegression {
   /**
    * Constructor for the 2D polynomial fitting
    *

src/regression/potential-regression.js

@@ -1,4 +1,4 @@
-import BaseRegression, { maybeToPrecision } from "ml-regression-base";
+import { BaseRegression, maybeToPrecision } from "ml-regression-base";
 import { PolynomialRegression } from "ml-regression-polynomial";
 
 /*
@@ -10,7 +10,7 @@ import { PolynomialRegression } from "ml-regression-polynomial";
  * @param {Number} M - The exponent of the potential fit.
  * @return {Number} A - The A coefficient of the potential fit.
  */
-export default class PotentialRegression extends BaseRegression {
+export class PotentialRegression extends BaseRegression {
   /**
    * @constructor
    * @param x: Independent variable